Coding techniques of image data in spatial domain

The compression and decompression of gray-level-image files in the spatial domain using three different methods is examined. The first method uses the average weights of neighboring pixels to calculate the value of the current one. The second method combines weights and a delta value to estimate the missing pixel. The purpose of the delta value is to enhance the quality at the edges. The third method uses adaptive vector quantization. Codebooks of representative vectors are generated for different portions of the image. The performance of the coder is estimated in terms of signal-to-noise ratio. Coding parameters such as vector dimension, number of representative vectors, and searching technique are discussed. Compression ratios are examined as a function of signal-to-noise ratio, and running time