RGBW image compression by low-complexity adaptive multi-level block truncation coding

Abstract

Frame memory compression is a widely used image compression technique that aims to reduce the size of the frame memory in display panels such as those containing LCD and OLED technologies. Recent LCD panels use the RGBW color domain to replace the traditional RGB domain in order to enhance the brightness of LCD panels with the addition of a white component. The additional component increases the size of the frame memory but necessitates an aggressive compression algorithm. This paper proposes a novel compression algorithm for RGBW components that improves the efficiency of block truncation coding (BTC), which is widely used for LCD overdrive. The proposed low-complexity adaptive multi-level block truncation coding (LAM-BTC) algorithm codes RGBW color data with a width of ten bits. It adaptively selects two-level BTC or four-level BTC to enhance the quality of the images, for which a low-complex level selection scheme is used. Four-level BTC in the proposed algorithm codes two representative values (RV) in four RVs and infers the other two RVs using inter-color correlation. In spite of the reduced complexity, the average peak signal-to-noise ratio (PSNR) of the proposed algorithm is 0.54 dB higher than that of the previous AM-BTC at a compression ratio of eight.