A widely used contrast enhancement method, the histogram equalization (HE) often produces images with unnatural appearances and visually disturbing artifacts because the HE compels the enhanced image to follow the uniform distribution. An adaptive histogram equalization using logarithmic mapping is presented, with a proposed algorithm based on a bin underflow and overflow method that achieves contrast enhancement by putting constraints on each histogram component differently. To incorporate characteristics of the human visual system, the logarithmic mapping function is used as constraint function, while the rate of contrast enhancement is controlled by determining the control parameters with the characteristics of the original image. The experimental results show that the proposed algorithm not only keeps the original histogram shape features, but also enhances the contrast effectively. Due to its simplicity, the proposed algorithm can be applied by simple hardware and processed in a real-time system.
The H.264/AVC (advanced video coding) is used in a wide variety of applications including digital broadcasting and mobile applications, because of its high compression efficiency. The variable block mode scheme in H.264/AVC contributes much to its high compression efficiency but causes a selection problem. In general, rate-distortion optimization (RDO) is the optimal mode selection strategy, but it is computationally intensive. For this reason, the H.264/AVC encoder requires a fast mode selection algorithm for use in applications that require low-power and real-time processing. A probable mode prediction algorithm for the H.264/AVC encoder is proposed. To reduce the computational complexity of RDO, the proposed method selects probable modes among all allowed block modes using removable SKIP mode distortion estimation. Removable SKIP mode distortion is used to estimate whether or not a further divided block mode is appropriate for a macroblock. It is calculated using a no-motion reference block with a few computations. Then the proposed method reduces complexity by performing the RDO process only for probable modes. Experimental results show that the proposed algorithm can reduce encoding time by an average of 55.22% without significant visual quality degradation and increased bit rate.