Efficient block prediction-based coding of computer screen images with precise block classification

This study presents a precise, one-pass block classification algorithm for efficient coding of computer screen images like power-point presentations, webpages and wall papers. The objective is to minimise the loss of visual quality of text during compression by separating text information which needs high spatial resolution than the pictures and background. It segments computer screen images into text/graphic, picture/background blocks by computing the statistical feature based on discrete wavelet transforms coefficients in the detail sub-bands of each 8×8 block, and then compresses the text/graphics pixels losslessly with a two-mode block prediction coding and the background pixels with the lossy JPEG algorithm. The proposed scheme performs accurate block classification of text information with different fonts, sizes and ways of arrangement from the background image, so that text/graphics blocks are compressed at higher quality than background image blocks. Experimental results show that the proposed method minimises block classification error and improves the value of peak signal-to-noise ratio significantly than standard JPEG, JPEG-2000 and H.264/AVC-I, while keeping competitive compression ratio and visually lossless quality of text information.