A classification method for adaptive transform image coding

Abstract

This paper introduces a new classification method, termed vector-scalar classification, where each D C T (ac) vector is indexed using vector quantization (VQ) on the energy vector of the corresponding D C T subvectors, and the subvectors each are then classified according t o the class assignment for the VQ. Vector-scalar classification achieves an average classification gain about 6.5 dB higher than block classification proposed by Chen and Smith [l], since VQ has high clustering performance and classification of subvectors can exploit compactness of D C T coefficients more efficiently. T h e complexity of this method is relatively low. For coding small images, a fixed-rate D C T coding system developed using vector-scalar classification is competitive with some best variable-rate coding systems reported in the literature, and the classification can capture most of the performance gain obtained by entropy coding.

Research on Agricultural Products Quality Control Based on Computer Vision Information Technology

“…Computer vision detection technology is a very practical NDT technology for agricultural products, the realization of nondestructive testing technology is the main image data for image scanner by computer for image segmentation, using function interpolation forms distinguish agricultural dimensions, comparing the size and quality standards [6,7]. The output value of image segmentation commonly uses two order upwind scheme and linear interpolation scheme.…”