Image processing problem: halftoning by using matrix and computing the averages.
ID: 3887547 • Letter: I
Question
Image processing problem: halftoning by using matrix and computing the averages. Please show the Matlab code (prefer typed for clarity) and explaination is greatly appreciated. Thanks in advance.
Title: Binary Image Rendering using Halftoning. Halftoning is a technique that uses patterns of black and white dots to simulate a grayscale image. It is useful when an output device can only print or display black or white. The figure below shows 3x3 patterns of black and white dots that you will use to represent blocks of 3x3 pixels in grayscale images. That is, the input will be a grayscale image whose pixels have values from 0 to 255 and the output will be an image that only contains two values, one corresponding to black and the other to white, 2 (Ignore the fact that the dots above are circular. They should really be square.) Your assignment a) In Matlab, write the function halftone that takes a grayscale image with values 0-255 as its input (this input should be a matrix, not a filename) and returns a binary (two-valued) image (again a matrix) as its output. The input and output should be of type uint8. Your function should use the 10 dot patterns above to transform the grayscale image to the binary image. You will have to decide on this transformation. Importantly, your input and output images should have the same size (number of pixels). Include the code for this function in your lab report.Explanation / Answer
Image processing can be broadly defined as the manipulation of signals which are inherently multidimensional. The most common such signals are photographs and video sequences. The goals of processing or manipulation can be (i) compression for storage or transmission; (ii) enhancement or restoration; (iii) analysis, recognition, and understanding; or (iv) visualization for human observers. The use of image processing techniques has become almost ubiquitous; they find applications in such diverse areas as astronomy, archaeology, medicine, video communication, and electronic games. Nonetheless, many important problems in image processing remain unsolved. It is the goal of this paper to discuss some of these challenging problems. In Section I, we mention a number of outstanding problems. Then, in the remainder of this paper, we concentrate on one of them: very-low-bit-rate video compression. This is chosen because it involves almost all aspects of image processing.