An adaptive orthogonal transform coding algorithm for images utilizing classification technique

An adaptive orthogonal transform coding algorithm utilizing the classification technique is presented. Coding efficiency for natural images can be improved by adjusting coding parameters in accordance with the local property of images. “Classification” is used to categorize small areas of an image into classes based on their characteristics. High coding efficiency results from changing coding parameters adaptively according to the classification index. Classification methods using ac energy, binary pattern and vector quantization index are compared, and the advantage of the classification method with the vector quantization technique is shown. Also, an orthogonal transform coding algorithm with an adaptive variable length coding method is proposed, and its structure and characteristics are described. A coding parameter normalization method to avoid mismatches between input images and coding parameters is also described. Coding experiments show excellent performance of this algorithm, for example, the number of bits for obtaining 40‐dB SNR of monochrome “GIRL” is 0.65 bits/pel, which is 20 percent smaller than conventional methods.