Research of Computer Desktop Image Compression Clustering Algorithm

The basis for the image algorithm is the Discrete Cosine Transform (DCT) which extracts spatial frequency information from the spatial amplitude samples. In this paper, an image compression k-means clustering algorithm based on block-based discrete cosine transform to compress computer desktop image is proposed. It divides computer screen image into 16×16 non-overlapping blocks, then each block is classified into text/graphic block, hybrid block or picture block. For text/graphic blocks with rich color, a color clustering algorithm is used to reduce the number of colors, text/graphic block is coded by lossless compression and hybrid block is coded by hybrid coding method. Experimental results indicated that the image by our proposed algorithm has higher Peak Signal to Noise Ratio (PSNR) and Structural Similarity (SSIM) than traditional algorithms.