The presence of haze in the atmosphere degrades the quality of images captured by visible camera sensors. The removal of haze, called dehazing, is typically performed under the physical degradation model, which necessitates a solution of an ill-posed inverse problem. To relieve the difficulty of the inverse problem, a novel prior called dark channel prior (DCP) was recently proposed and has received a great deal of attention. The DCP is derived from the characteristic of natural outdoor images that the intensity value of at least one color channel within a local window is close to zero. Based on the DCP, the dehazing is accomplished through four major steps: atmospheric light estimation, transmission map estimation, transmission map refinement, and image reconstruction. This four-step dehazing process makes it possible to provide a step-by-step approach to the complex solution of the ill-posed inverse problem. This also enables us to shed light on the systematic contributions of recent researches related to the DCP for each step of the dehazing process. Our detailed survey and experimental analysis on DCP-based methods will help readers understand the effectiveness of the individual step of the dehazing process and will facilitate development of advanced dehazing algorithms.

H.264/AVC provides various useful features such as improved coding efficiency and error robustness. These features enable mobile devices to adopt H.264 standard to achieve effective video communications. However, the encoder complexity is greatly increased mainly due to motion estimation (ME) and mode decision. In this paper, we propose a new scheme to jointly optimize intermode selection and ME using the multiresolution analysis. Experimental results show that the proposed method is over 3 times faster than other existing methods while maintaining the coding efficiency.

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In this paper, a co-design method for JPEG2000 video compression system using DSP and FPGA is presented. By profiling the complexity of JPEG2000 algorithm, it is noticed that a MQ-coder is the most complex part. Thus, we implement the MQ-coder on FPGA for the parallel processing using VHDL to reduce the complexity. In order to verify the performance of the MQ-coder, JBIG2 standard test vector and images are used. The experimental results show that the proposed MQ-coder enhances the processing time approximately 3 times compared with the previous software MQ-coder.

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