Introduction to image data compression; (6). Image data coding algorithm. III. Vector quantization.

Vector Quantization Based Image Compression

An image compression method combining discrete wavelet transform (DWT) and vector quantization (VQ) is presented. First, a three-level DWT is performed on the original image resulting in ten separate sub bands. These sub bands are then vector quantized. VQ indices are Huffman coded to increase the compression ratio. Lloyd extended scalar quantization technique is used to design memory less vect...

Vector Quantization for Image Compression-Concept Quantization

Self-organized Color Image Quantization for Color Image Data Compression

This paper presents a neural network approach to image color quantization and hence image data compression. Self-organizing feature maps form a basis for general vector quantization and this is applied to the tristimulus color values of image pixels. For image telecommunication systems such as videoconferencing, it Is desirable to constrain the encoder to a single pass of the image using the no...

Vector Quantization using Genetic &Means Algorithm for Image Compression

In Vector Quantization (VQ), minimization of Mean Square Error (MSE) between code book vectors and training vectors is a non-linear problem. Traditional LBG type of algorithms converge to a local minimum, which depends on the initial code book. While most of the efforts in VQ have been directed towards designing efficient search algorithms for code book, little has been done in evolving a proce...

Scattered Data Coding in Digital Image Compression

This paper concerns digital image compression using adaptive thinning algorithms. Adaptive thinning is a recursive point removal scheme which works with decremental Delaunay triangulations. When applied to digital images, adaptive thinning returns a scattered set of most significant pixels. This requires efficient and customized methods for coding these pixels (but not their connectivities). To...