China
Africa
Explore chapters and articles related to this topic
Video compression
Published in David Austerberry, The Technology of Video and Audio Streaming, 2013
The fractal compression technique relies on the fact that, in certain images, parts of the image resemble other parts of the same image. Similar sections of an image are located, and then the fractal algorithm is applied. Patents have restricted its use, and since wavelet compression offers better efficiency it has been the focus of more intense development effort.
Image Compression
Published in Scott E. Umbaugh, Digital Image Processing and Analysis, 2017
Model-based or intelligent compression works by modeling objects in the image and storing object descriptions.Fractal methods are an example of model-based techniques.Fractal compression is based on the idea that various regions in the image are self-similar, which means that one subimage can be represented as a skewed, stretched, rotated, scaled and/or translated version of another subimage.The mathematical operations, skew, stretch, scale, rotate, and translate, are called affine transformations and can be represented by the following general equations: r′=k1r+k2c+k3c′=k4r+k5c+k6 where r’ and c’ are the new coordinates, and ki are constants.Fractal image compression divides an image into subimages, and selects some to serve as models called range regions to map to the domain regions which represent the entire image.These range regions are the fractals, which are like basis images that can undergo affine transformations and be assembled into a good representation of the image.The compressed file stores the fractals and the necessary affine transformation coefficients.Model-based methods can provide high compression ratios, but have complex and costly compression methods.
An image compression model via adaptive vector quantization: hybrid optimization algorithm
Published in The Imaging Science Journal, 2020
Pratibha Pramod Chavan, B. Sheela Rani, M. Murugan, Pramod Chavan
Image compression is a method of removing or decreasing duplication in image representation in order to save communication and storage. As per the reconstructed image quality, the compression methods are usually classified as lossless or lossy [1,2]. Lossless compression guarantees that the rebuilt image will be a good replacement for the original. The compression ratio of this sort of compression is usually lower than that lossy compression. Lossless compression techniques include RLE, LZW, and entropy coding [3,4]. To achieve a higher compression ratio or a larger decrement data, some nonredundant information is discarded in the lossy compression. As a consequence, the reconstructed image is distorted at cost . Lossy compression is represented by JPEG, SPIHT, and fractal compression [5,6].