short notes od digital image processing, Schemes and Mind Maps of Biomedical Engineering

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EC 8093 - DIGITAL IMAGE PROCESSING NOTES

1. To become familiar with digital image fundamentals & get exposed to simple image enhancement techniques in Spatial and Frequency domain.
2. To learn concepts of degradation function and restoration techniques & study the image segmentation and representation techniques.
3. To become familiar with image compression and recognition methods UNIT I - DIGITAL IMAGE FUNDAMENTALS Steps in Digital Image Processing – Components – Elements of Visual Perception – Image Sensing and Acquisition – Image Sampling and Quantization – Relationships between pixels - Color image fundamentals - RGB, HSI models, Two-dimensional mathematical preliminaries, 2D transforms - DFT, DCT. UNIT II IMAGE ENHANCEMENT Spatial Domain: Gray level transformations – Histogram processing – Basics of Spatial Filtering– Smoothing and Sharpening Spatial Filtering, Frequency Domain: Introduction to Fourier Transform– Smoothing and Sharpening frequency domain filters – Ideal, Butterworth and Gaussian filters, Homomorphic filtering, Color image enhancement. UNIT III IMAGE RESTORATION Image Restoration - degradation model, Properties, Noise models – Mean Filters – Order Statistics – Adaptive filters – Band reject Filters – Band pass Filters – Notch Filters – Optimum Notch Filtering – Inverse Filtering – Wiener filtering. UNIT IV IMAGE SEGMENTATION Edge detection, Edge linking via Hough transform – Thresholding - Region based segmentation – Region growing – Region splitting and merging – Morphological processing- erosion and dilation, Segmentation by morphological watersheds – basic concepts – Dam construction – Watershed segmentation algorithm. UNIT V IMAGE COMPRESSION AND RECOGNITION Need for data compression, Huffman, Run Length Encoding, Shift codes, Arithmetic coding, JPEG standard, MPEG. Boundary representation, Boundary description, Fourier Descriptor, Regional Descriptors – Topological feature, Texture - Patterns and Pattern classes - Recognition based on matching. OUTCOMES: At the end of the course, the students should be able to:
4. Know and understand the basics and fundamentals of digital image processing, such as digitization, sampling, quantization, and 2D-transforms.
5. Operate on images using the techniques of smoothing, sharpening and enhancement &understand the restoration concepts and filtering techniques.
6. Learn the basics of segmentation, features extraction, compression and recognition methods for color models. TEXT BOOKS: 1.Rafael C. Gonzalez, Richard E. Woods, Digital Image Processing, Pearson, 3Edition, 2010. 2.Anil K. Jain, Fundamentals of Digital Image Processing, Pearson, 2002. REFERENCES 1.Kenneth R. Castleman, Digital Image Processing, Pearson, 2006. 2.Rafael C. Gonzalez, et al, Digital Image Processing using MATLAB, Pearson 2011. 3.D,E. Dudgeon et al,Multidimensional Digital Signal Processing, Prentice Hall Professional Technical Reference, 1990. 4.William K. Pratt, Digital Image Processing, John Wiley, New York, 2002 5.Milan Sonka et al,Image processing, analysis and machine vision, Brookes/Cole, Vikas Publishing House, 2nd edition, 1999

LECTURE NOTES

UNIT I - DIGITAL IMAGE FUNDAMENTALS

EC8093-DIP

EC8093 DIGITAL IMAGE PROCESSING

OBJECTIVES:

13. List the applications of color models

1. RGB model--- used for color monitors & color video camera
2. CMY model---used for color printing
3. HIS model----used for color image processing
4. YIQ model---used for color picture transmission 14. Differentiate Luminance and Chrominance A. Luminance: received brightness of the light, which is proportional to the total energy in the visible band. B.Chrominance: describe the perceived color tone of a light, which depends on the wavelength composition of light, chrominance is in turn characterized by two attributes – hue and saturation. 15. Show the block diagram of a general purpose Digital Image Processing system.

16. Write the different combinations of colours in additive color mixing. Red + Green = Yellow, Red + Blue = Magenta Blue + Green = Cyan, Red + Blue + Green = White 17. What are the two ways of mixing of colours? Mixing of colours can be done by two ways: (i) Additive mixing, (ii)Subtractive mixing 18. What do you mean by saturation and chrominance? Saturation: Saturation refers to the spectral purity of the color light. Chrominance: Hue and Saturation of a color put together is known as chrominance. 19. State Grassman’s law. The brightness impression produced by the three primary colours that constitute the single light. This property of the eye generating a response which depends on the algebraic sum of the Blue, Red and Green .This forms the basis of color signal generation is called “Grassman’s law”. 20. List out the factors that affect tonal gradation of the reproduced picture. a) Brightness b) Contrast c) Viewing distance d) Luminance e) Hue and Saturation. 21. Write the basic principle of Television camera tube. The camera pickup and converts optical information of the scene into electrical energy form may be called as eye of the television system. 22. Define Contrast and Hue. Contrast: This is the difference in light intensity between black and white parts of the picture over and above the average brightness level. Hue: This is the predominant spectral color of the received light. Thus the color of any object is distinguished by its hue or tint. 23. Define Image Quantization. An image may be continuous with respect to the x- and y- co-ordinates and also in amplitude digitizing the amplitude value is called Quantization. 24. Define Image Sampling. The process of converting continuous spatial co-ordinates into its digitized form is called as sampling.

Saveetha Engineering College 6

There are three types of adjacency. They are a. 4-adjacency,b.8-adjacency,c.m-adjacency

36. Name some application of Digital Image Processing. 1. Remote sensing 2. Image transmission and storage for business applications. 3. Medical processing 4. Radar and Sonar 5. Acoustic Image Processing 6. Robotics 7. Automated inspection of industrial parts. 37. Define Euclidean distance. The Euclidean distance between p and q is defined as D(p, q) = [(x – s)^2 + (y – t)^2 ]1/2. 38. Define City – block distance. The D 4 distance, also called City-block distance between p and q is defined as D 4 (p, q) = |x – s| + |y – t|. 39. Give the formula for calculating D4 and D8 distance. D4 distance (city block distance) is defined by D4 (p, q) = |x-s| + |y-t| D8 distance (chess board distance) is defined by D8 (p, q) = max (|x-s|, |y-t|). 40. What is geometric transformation? Transformation is used to alter the co-ordinate description of image. The basic geometric transformations are 1. Image translation 2. Scaling 3. Image rotation 41. What is image translation and scaling? Image translation means reposition the image from one co-ordinate location to another along straight line path. Scaling is used to alter the size of the object or image (ie) a co-ordinate system is scaled by a factor. 42. What is Image Transform? And what is the need for transform? An image can be expanded in terms of a discrete set of basis arrays called basis images. These basis images can be generated by unitary matrices. Alternatively, a given NxN image can be viewed as an N^2x1 vectors. An image transform provides a set of coordinates or basis vectors for vector space. The term image transfer usually refers to a class of unitary matrices used for representing images.The need for transform is most of the signals or images are time domain signal(ie) signals can be measured with a function of time. This representation is not always best. For most image processing applications anyone of the mathematical transformation are applied to the signal or images to obtain further information from that signal. 43. Define the term Luminance Luminance measured in lumens (lm), gives a measure of the amount of energy an observer perceiver from a light source. 44. What are the applications of transform? 1) To reduce band width 2) To reduce redundancy 3) To extract feature. 45. What are the properties of unitary transform?

1. Determinant and the Eigen values of a unitary matrix have unity m a g n i t u d e
2. The entropy of a random vector is preserved under a unitary Transformation
3. Since the entropy is a measure of average information, this means information is preserved under a unitary transformation.

46. Define Weber ratio The ratio of increment of illumination to background of illumination is called as Weber ratio.(ie) ∆ i/i

1. If the ratio (∆i/i) is small, then small percentage of change in intensity is needed (ie) good brightness adaptation.
2. If the ratio (∆i/i) is large, then large percentage of change in intensity is needed (ie) poor brightness adaptation. 47. What is meant by mach band effect? Mach band effect means the intensity of the stripes is constant. Therefore it preserves the brightness pattern near the boundaries, these bands is called as mach band effect. 48. What is simultaneous contrast? The region reserved brightness not depends on its intensity but also on its background. All centres square have same intensity. However they appear to the eye to become darker as the background becomes lighter. 49. What is meant by illumination and reflectance? Illumination is the amount of source light incident on the scene. It is represented as i(x, y).Reflectance is the amount of light reflected by the object in the scene. It is represented by r(x, y). 50. Find the number of bits required to store a 256 X 256 image with 32 gray levels?

32 gray levels = 2^5 = 5 bits, 256 * 256 * 5 = 327680 bits.

51. Write the expression to find the number of bits to store a digital image The number of bits required to store a digital image is b=M X N X k,

1. Image acquisition is the first process in the digital image processing. Note that acquisition could be as simple as being given an image that is already in digital form. Generally, the image acquisition stage involves pre-processing, such as scaling. 2. The next step is image enhancement , which is one among the simplest and most appealing areas of digital image processing. Basically, the idea behind enhancement techniques is to bring out detail that is obscured, or simply to highlight certain features of interest in an image. A familiar example of enhancement is when we increase the contrast of an image because “it looks better.” It is important to keep in mind that enhancement is a very subjective area of image processing. 3. Image restoration is an area that also deals with improving the appearance of an image. However, unlike enhancement, which is subjective, image restoration is objective, in the sense that restoration techniques tend to be based on mathematical or probabilistic models of image degradation. Enhancement, on the other hand, is based on human subjective preferences regarding what constitutes a “good” enhancement result.i.e remove noise and restores the original image 4. Color image processing is an area that has been gaining in importance because of the significant increase in the use of digital images over the Internet. Color image processing involves the study of fundamental concepts in color models and basic color processing in a digital domain. Image color can be used as the basis for extracting features of interest in an image. 5. Wavelets are the foundation for representing images in various degrees of resolution. In particular, wavelets can be used for image data compression and for pyramidal representation, in which images are subdivided successively into smaller regions. 6. Compression, as the name implies, deals with techniques for reducing the storage required saving an image, or the bandwidth required transmitting it. Although storage technology has improved significantly over the past decade, the same cannot be said for transmission capacity. This is true particularly in uses of the Internet, which are characterized by significant pictorial content. Image compression is familiar (perhaps

inadvertently) to most users of computers in the form of image file extensions, such as the jpg file extension used in the JPEG (Joint Photographic Experts Group) image compression standard.

7. Morphological processing deals with tools for extracting image components that are useful in the representation and description of shape. The morphological image processing is the beginning of transition from processes that output images to processes that output image attributes. 8. Segmentation procedures partition an image into its constituent parts or objects. In general, autonomous segmentation is one of the most difficult tasks in digital image processing. A rugged segmentation procedure brings the process a long way toward successful solution of imaging problems that require objects to be identified individually. On the other hand, weak or erratic segmentation algorithms almost always guarantee eventual failure. In general, the more accurate the segmentation, the more likely recognition is to succeed. 9. Representation and description almost always follow the output of a segmentation stage, which usually is raw pixel data, constituting either the boundary of a region (i.e., the set of pixels separating one image region from another) or all the points in the region itself. 10. Recognition is the process that assigns a label (e.g., “vehicle”) to an object based on its descriptors. Recognition topic deals with the methods for recognition of individual objects in an image. 2. Explain the Components of an Image Processing System Figure shows the basic components comprising a typical general-purpose system used for digital image processing. The function of each component is discussed in the following paragraphs, starting with image sensing. 1. With reference to sensing , two elements are required to acquire digital images. The first is a physical device that is sensitive to the energy radiated by the object we wish to image. The second, called a digitizer, is a device for converting the output of the physical sensing device into digital form. For instance, in a digital video camera, the sensors produce an electrical output proportional to light intensity. The digitizer converts these outputs to digital data. 2. Specialized image processing hardware usually consists of the digitizer just mentioned, plus hardware that performs other primitive operations, such as an arithmetic logic unit (ALU) that performs arithmetic and logical operations in parallel on entire images. ALU is used is in averaging images as quickly as they are digitized, for the purpose of noise reduction. This unit performs functions that require fast data throughputs (e.g., digitizing and averaging video images at 30 frames/s) 3. The computer in an image processing system is a general-purpose computer and can range from a PC to a supercomputer. For dedicated applications, 4. Software for image processing consists of specialized modules that perform specific tasks.

3. Image retrieval - Seek for the image of interest.
4. Measurement of pattern – Measures various objects in an image.
5. Image Recognition – Distinguish the objects in an image. **Image Processing Types:
6. Analog Image Processing:** Analog or visual techniques of image processing can be used for the hard copies like printouts and photographs. Image analysts use various fundamentals of interpretation while using these visual techniques. The image processing is not just confined to area that has to be studied but on knowledge of analyst. Association is another important tool in image processing through visual techniques. So analysts apply a combination of personal knowledge and collateral data to image processing. 2. Digital Image Processing: Digital Processing techniques help in manipulation of the digital images by using computers. As raw data from imaging sensors from satellite platform contains deficiencies. To get over such flaws and to get originality of information, it has to undergo various phases of processing. The three general phases that all types of data have to undergo while using digital technique are Pre- processing, enhancement and display, information extraction.

Applications of Image Processing:

1. Intelligent Transportation Systems - This technique can be used in Automatic number plate recognition and Traffic sign recognition.

2. Remote Sensing - For this application, sensors capture the pictures of the earth’s surface in remote sensing satellites or multi – spectral scanner which is mounted on an aircraft. These pictures are processed by transmitting it to the Earth station. Techniques used to interpret the objects and regions are used in flood control, city planning, resource mobilization, agricultural production monitoring, etc.
3. Moving object tracking - This application enables to measure motion parameters and acquire visual record of the moving object. The different types of approach to track an object are: · Motion based tracking · Recognition based tracking
4. Defense surveillance – Aerial surveillance methods are used to continuously keep an eye on the land and oceans. This application is also used to locate the types and formation of naval vessels of the ocean surface. The important duty is to divide the various objects present in the water body part of the image. The different parameters such as length, breadth, area, perimeter, compactness are set up to classify each of divided objects. It is important to recognize the distribution of these objects in different directions that are east, west, north, south, northeast, northwest, southeast and south west to explain all possible formations of the vessels. We can interpret the entire oceanic scenario from the spatial distribution of these objects.
5. Biomedical Imaging techniques - For medical diagnosis, different types of imaging tools such as X- ray, Ultrasound, computer aided tomography (CT) etc are used. The diagrams of X- ray, MRI, and computer aided tomography (CT) are given below.

Some of the applications of Biomedical imaging applications are as follows: · Heart disease identification– The important diagnostic features such as size of the heart and its shape are required to know in order to classify the heart diseases. To improve the diagnosis of heart diseases, image analysis techniques are employed to radiographic images. · Lung disease identification – In X- rays, the regions that appear dark contain air while region that appears lighter are solid tissues. Bones are more radio opaque than tissues. The ribs, the heart, thoracic spine, and the diaphragm that separates the chest cavity from the abdominal cavity are clearly seen on the X-ray film.

not only used in the clinical setting, it is increasingly playing a role in many research investigations. Magnetic Resonance Imaging (MRI) utilizes the principle of Nuclear Magnetic Resonance (NMR) as a foundation to produce highly detailed images of the human body. The patient is firstly placed within a magnetic field created by a powerful magnet. Image File Formats: Image file formats are standardized means of organizing and storing digital images. Image files are composed of digital data in one of these formats that can be for use on a computer display or printer. An image file format may store data in uncompressed, compressed, or vector formats. Image file sizes: In raster images, Image file size is positively correlated to the number of pixels in an image and the color depth, or bits per pixel, of the image. Images can be compressed in various ways, however. Major graphic file formats The two main families of graphics Raster and Vector.

Raster formats

1. JPEG/JFIF JPEG (Joint Photographic Experts Group) is a compression method; JPEG- compressed images are usually stored in the JFIF (JPEG File Interchange Format) file format. JPEG compression is (in most cases) lossy compression. The JPEG/JFIF filename extension is JPG or JPEG. 2. JPEG 2000 JPEG 2000 is a compression standard enabling both lossless and lossy storage. The compression methods used are different from the ones in standard JFIF/JPEG; they improve quality and compression ratios, but also require more computational power to process. JPEG 2000 also adds features that are missing in JPEG. 3. TIFF The TIFF (Tagged Image File Format) format is a flexible format that normally saves 8 bits or 16 bits per color (red, green, blue) for 24-bit and 48-bit totals, respectively, usually using either the TIFF or TIF filename extension.TIFFs can be lossy and lossless;

4. GIF GIF (Graphics Interchange Format) is limited to an 8-bit palette, or 256 colors. This makes the GIF format suitable for storing graphics with relatively few colors such as simple diagrams, shapes, logos and cartoon style images. 5.BMP The BMP file format (Windows bitmap) handles graphics files within the Microsoft Windows OS. Typically, BMP files are uncompressed, hence they are large; the advantage is their simplicity and wide acceptance in Windows programs. 6.PNG The PNG (Portable Network Graphics) file format was created as the free, open- source successor to GIF. The PNG file format supports 8 bit paletted images (with optional transparency for all palette colors) and 24 bit truecolor (16 million colors).

3. Explain the principle and working of Vidicon digital camera with neat diagram (Image sensing and Acquisition) A digital camera is used to convert the optical information into a corresponding electrical signal, the amplitude which varies in accordance with the variations of brightness. Photoelectric Effects The two photoelectric effects used for converting variations of light intensity into electrical variations are (i) photoemission and (ii) photoconductivity. Photo emission : Certain metals emit electrons when light falls on their surface. These emitted electrons are called photoelectrons and the emitting surface a photocathode. Light consists of small bundles of energy called photons. When light is made incident on a photocathode, the photons give away their energy to the outer valence electrons to allow them to overcome the potential-energy barrier at the surface. The number of electrons which can overcome the potential barrier and get emitted depends on the light intensity. Alkali metals are used as photocathode because they have very low work-function. Cesium- silver or bismuth-silver-cesium oxides are preferred as photo emissive surfaces because they are sensitive to incandescent light and have spectral response very close to the human eye. Photo conductivity :-The second method of producing an electrical image is by photoconduction, where the conductivity or resistivity of the photosensitive surface varies in proportion to the intensity of light focused on it. In general the semiconductor metals including selenium, tellurium and lead with their oxides have this property known as photoconductivity. The variations in resistance at each point across the surface of the material are utilized to develop a varying signal by scanning it uniformly with an electron beam

Fig-Photo emission

Fig-Photo conductivity Types of camera tubes: 1) orthicon 2) vidicon 3) Plumbicon.

electrons hitting the screen may cause stray electron field &may grid tangentially which may cause defocusing and loss resolution. The beam should strike at right angles with screen.

3. Electron gun multiplier. When the surface of a metal is bombarded by incident electrons having high velocities secondary emissions takes place. Camera tubes make use of secondary emissions to amplify small amount of photoelectric current that is later employed to develop video signal. The electron multiplier is a collection of anode cathode electrodes called dynodes. The electrons are accelerated by the positive potential of the dynode. The number of electrons available is multiplied each time the secondary electron strikes the emitting surface of the next positive dynode. The current amplification is noise free as it does not have any active or passive components.

Fig-Dgital camera(VIDICON)

Fig-Digital camera (VIDICON) Light from the scene is focused on a photosensitive surface known as the image plate, and the optical image thus formed with a lens system represents light intensity variations of the scene. The photoelectric properties of the image plate then convert different light intensities into corresponding electrical variations. In addition to this photoelectric conversion whereby the optical information is transduced to electrical charge distribution on the photosensitive image plate, it is necessary to pick-up this information as fast as possible

4. Explain in Detail the structure of the Human eye and also explain the image formation in the eye. (OR) Explain the Elements of Visual Perception. Visual Perception: Means how an image is perceived by a human observer The Shape of the human eye is nearly a sphere with an Average diameter = 20mm.It has 3 membranes: 1. Cornea and Sclera – outer cover 2. Choroid 3. Retina -enclose the eye Cornea : tough, transparent tissue covers the anterior surface of the eye. Sclera : Opaque membrane, encloses the remainder of the optic globe Choroid : Lies below the sclera .It contains a lot of blood vessels providing nutrition to the eye. The Choroid coat is heavily pigmented and hence helps to reduce the amount of extraneous light entering the eye and the backscatter within the optical globe. At the anterior part, the choroid is divided into Ciliary body and the Iris diaphragm.

Structure of the Human Eye:

The Iris contracts or expands according to the amount of light that enters into the eye. The central opening of the iris is called pupil, which varies from 2 mm to 8 mm in diameter. Lens is made of concentric layers of fibrous cells and is suspended by fibers that attach to the Ciliary body. It contains 60-70% of water, 6 % fat and more protein. Lens is colored by yellow pigment which increases with eye. Excessive clouding of lens can lead to poor or loss of vision, which is referred as Cataracts. Retina: Innermost membrane of the eye which lines inside of the wall’s entire posterior portion. When the eye is properly focused, light from an object outside the eye is imaged on the retina. It consists of two photo receptors.