LAUSR

A smart device such as a television, tablet, and smartphone, often displays a compound image consisting of various types of sub-images, including texts and pictures. A text image displayed on a smart device is composed of red, green, and blue (RGB) sub-pixels having strong correlation among them. This paper proposes a new compression algorithm, called sub-pixel gradient compression (SPGC), that makes use of the correlation in a text in order to improve its compression efficiency. The initial step of the proposed algorithm converts a text into a de-colorized image in which RGB sub-pixels vary gradually. The de-colorization is a necessary step to further enhance the correlation among RGB sub-pixels, and thereby improving the compression efficiency. From the de-colorized text, the next step estimates the slopes of the gradual variations among sub-pixels and then encodes the slopes and their associated information as a bitstream. SPGC is a relatively simple algorithm because its main operation is the estimation of sub-pixel gradients and the precise estimation of the gradients makes it possible to reduce a degradation of the quality of the texts. Experimental results show that SPGC maintains lower complexity and a higher compression ratio than the compression standards including JPEG, JPEG-2000, H.264, or HEVC.