Digital image processing
- 2. CONTENTS • INTRODUCTION • FORMATION OF DIGITAL IMAGE • AD CONVERSION • WORKING IN TELEVISION • APPLICATIONS • CONCLUSION
- 3. INTRODUCTION TO DIP • Digital image processing deals with manipulation of digital images through a digital computer. It is a subfield of signals and systems but focus particularly on images. The most common example is Adobe Photoshop
- 4. IMAGE • An image is mathematical function f(x,y) where x and y are the two co-ordinates horizontally and vertically. • The value of f(x,y) at any point is gives the pixel value at that point of an image.
- 5. PIXEL • Pixel is the smallest element of an image. • The value of a pixel at any point correspond to the intensity of the light photons striking at that point. • Total number of pixels = number of rows ( X ) number of columns. • Size of an image = rows * cols * bpp
- 6. TYPES OF IMAGES • BINARY IMAGE • GRAY SCALE IMAGE • 16 BIT COLOR IMAGE • 24 BIT COLOR IMAGE
- 7. BINARY IMAGE FORMAT • The binary image as it name states, contain only two pixel values. • 0 and 1.
- 8. GRAY SCALE FORMAT • The range of the colors in 8 bit vary from 0-255. Where 0 stands for black, and 255 stands for white, and 127 stands for gray color. there would be two dimensional matrix in behind with values ranging between 0 and 255.
- 9. 16 BIT COLOR FORMAT • It is a color image format. It has 65,536 different colors in it. It is also known as High color format. • 16 bit format is actually divided into three further formats which are Red , Green and Blue. 5 bits for R, 5 bits for G, 5 bits for B.5 bits for R, 6 bits for G, 5 bits for B. • 4 bits for R, 4 bits for G, 4 bits for B, 4 bits for alpha channel. • Or some distribute it like this • 5 bits for R, 5 bits for G, 5 bits for B, 1 bits for alpha channel.
- 10. 24 BIT COLOR FORMAT • 24 bit color format also known as true color format. 8 bits for R, 8 bits for G, 8 bits for B. • a 24 bit image has three different matrices of R, G, B.
- 11. FORMATION OF DIGITAL IMAGE • image is captured by camera • sunlight is source of energy • a sensor array is used for the acquisition of the image. • continuous voltage signal is generated by the amount of sensed data
- 12. AD CONVERSION • digital image processing deals with digital images, that are digital signals. • storage of analog signals is difficult • 2 MAIN METHODS: 1. sampling 2. quantization
- 13. SAMPLING QUANTIZATION • sampling as its name suggests can be defined as take samples. sampling is done on an independent variable. • quantization as its name suggest can be defined as dividing into quanta (partitions). quantization is done on dependent variable. it is opposite to sampling.
- 14. APPLICATION IN TELEVISION • image is 2d • to convert into 3d move image along time axis • helps to perceive the depth of different objects on a screen. • a video is nothing else but two dimensional pictures move over time dimension.
- 15. ZOOMING • Zooming simply means enlarging a picture in a sense that the details in the image became more visible and clear. Zooming an image has many wide applications ranging from zooming through a camera lens, to zoom an image on internet e.t.c. • Methods: 1. Pixel replication or (Nearest neighbor interpolation) 2. Zero order hold method
- 16. PIXEL REPLICATION • Each pixel is replicated in this method n times row wise and column wise and you got a zoomed image.
- 17. ZERO ORDER HOLD METHOD • In zero order hold method, pick two adjacent elements from the rows respectively and then add them and divide the result by two, and place their result in between those two elements. • We first do this row wise and then we do this column wise.
- 18. BRIGHTNESS • It can be defined as the amount of energy output by a source of light relative to the source we are comparing it to. • Brightness can be simply increased or decreased by simple addition or subtraction, to the image matrix.
- 19. CONTRAST • Contrast can be simply explained as the difference between maximum and minimum pixel intensity in an image
- 20. APPLICATIONS OF DIP • Image sharpening and restoration • Medical field • Remote sensing • Transmission and encoding • Machine/Robot vision • Color processing • Pattern recognition • Video processing • Microscopic Imaging
- 21. CONCLUSION • There are many applications based on digital image processing in today’s world • In the nearest future everything will be operated or controlled based on DIP applications