Quantization Parameters Selection of JPEG XR Based on Subjective Quality
Liu Zhi-yua · Jisuanji gongcheng · 2014
This paper proposes an encoding method with improving compression efficiency based on the standard of JPEG XR image. This method designs an adaptive quantization parameters selection algorithm based on image content by using the perception features of Human Visual System(HVS). According to the Just Noticeable Difference(JND) model, the macro blocks in the process of image compression are divided into 6 types by local texture and local brightness. Each type is assigned different quantization parameters of Direct Current(DC), Low Pass(LP) and High Pass(HP) coefficients adaptively, which distributes the bit rate of the entire image reasonably according to the texture complexity and brightness. Therefore, higher compression efficiency and lower rate are achieved with the same subjective quality. Experimental result show the proposed algorithm obtains a 10% higher compression efficiency compared with fixed quantization parameters algorithm.