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Image Compression Binary Image Compression. Contents. Run-length coding Predictive coding READ code Block coding. Binary images. Binary images consist only of two colors, black and white. The probability distribution of the alphabet is often
Image Compression. Signals and image processing by computer Winter 2012-13 Yael Erez. Binary Images. Bit Map Very simple Representation size = image size Large memory. Coding Scheme. image. code. Encode. code. image. Decode. Binary Images Encoding. Run Length
Image Compression. Mohamed N. Ahmed, Ph.D. Steve Weed. Image Compression. Everyday an enormous amount of information is stored, processed, and transmitted Financial data Reports Inventory Cable TV Online Ordering and tracking. Image Compression.
Image Compression. Reference.  Gonzalez and Woods, Digital Image Processing. Objective. Reduce the number of bytes required to represent a digital image Redundant data reduction Remove patterns Uncorrelated data confirms redundant data elimination Auto correlation?.
Image Compression. Mohamed N. Ahmed, Ph.D. Image Compression. Everyday an enormous amount of information is stored, processed, and transmitted Financial data Reports Inventory Cable TV Online Ordering and tracking. Image Compression.
Image compression. Image Compression. Why? Reducing transportation times Reducing file size A two way event - compression and decompression. Compression categories. Compression = Image coding Still-image compression Compression of moving image. Point to Point. Interframe Processing.
Image Compression. Chapter 8. 1 Introduction and background. The problem: Reducing the amount of data required to represent a digital image. Compression is achieved by removing the data redundancies: Coding redundancy Interpixel redundancy Psychovisual redundancy.
Image Compression. Data and information. Data is not the same thing as information . Data is the means with which information is expressed. The amount of data can be much larger than the amount of information. Data that provide no relevant information = redundant data or redundancy .
Image Compression. Image Compression. The goal of image compression is to reduce the amount of data required to represent a digital image. Image Compression (cont’d). Lossless Information preserving Low compression ratios Lossy Not information preserving High compression ratios