Lossless binary image compression using logic functions and spectra

A new approach for lossless compression of medical images has been proposed. After preprocessing, the image is split into bit planes to which the compressed technique is applied. These bit planes can be expressed as ordered binary decision diagrams (OBDD) and coding. This approach compared well with WINZIP in terms of compression ratio.

Medical Image Compression Based on Ordered Binary Decision Diagrams

Switching theoretic approach to image compression

A novel approach for the lossless compression of images is presented. After preprocessing, the image is split into bit planes which are then divided into smaller blocks. Mixed blocks are converted to Boolean switching functions and then subjected to minimization to arrive at a compact representation, leading to possible data compression. Blocks are then classified into distinct events based on the outcome of logic minimization. A Huffman code is constructed and the blocks are encoded suitably. This approach provides a framework to incorporate various possible switching theoretic techniques into the basic coding scheme proposed by us. This paper also shows that logic minimization can be used to handle blocks of larger size, than practically possible with Huffman coding, to yield significant compression on gray-level images. Our approach compares well with JPEG in terms of compression ratio.

/pdf/lossless-compression-of-images-using-logic-minimization-4ex5nrivyl.pdf

Lossless Compression Of Images Using Logic Minimization

Lossless compression of images is important in fields like medical imaging and remote sensing. There are only a small number of good algorithms known to date for lossless image compression. We present a lossless image compression scheme which uses the concepts of logic coding and auto-adaptive block coding to obtain a scheme which performs comparable to the JPEG standard. The scheme reaches the best possible value of compression automatically, unlike the case of JPEG which gives a range of compression, based on available predictors.

/pdf/lossless-compression-of-images-using-minterm-coding-i2i7aboeve.pdf

Lossless compression of images using minterm coding

We propose a novel approach for the lossless compression of binary images using logic minimization. The image is divided into windows or blocks of size r/spl times/c pixels and each block is transformed into a Boolean switching function in cubical form, treating the pixel values as output of the function. Compression is performed by minimizing these switching functions using ESPRESSO, a cube-based two-level logic minimizer. To reduce the bits required to encode the minimized cubes (product terms), a code set which satisfies the prefix property is used. If this technique fails to produce compression for a window, the pixels are stored as such. The main motivation of the work has been to investigate the potential of logic minimization as a tool for image data compression. Our technique outperforms UNIX compress in terms of compression ratio on most of the test images. The compression scheme is relatively slower while the decompression time is comparable to that of UNIX compress.

/pdf/logic-minimization-based-approach-for-compressing-image-data-29g2q80cac.pdf

Logic minimization based approach for compressing image data

We propose a novel approach for the lofsless compression of binary images using logic minimization. The image is divided into windows or blocks of size r x c pixels and each block is transformed into a Boolean .switching function in cubical form, treating the pixel values as output of the function. Compression is performed by minimizing these switching functions using ESPRESSO, a cube-based two-level logic minimizer. To reduce the bits required to encode the minimized cubes (product terms), a code set which satisfies the prefix property is used. If this technique fails to produce compression for a window, the pixels are stored as such. The main motivation of the work has been to investigate the potential of logic minimization as a tool for image data compression. Our technique outperforms UNIX compress in terms of compression ratio on most of the test images. The compression scheme is relatively slower while the decompression time is comparable to that of UNIX compress.

Wen Feng

Papers

Switching theoretic approach to image compression

Logic minimization based approach for compressing image data

Logic Minimization Based proach for CO ata