Research On Algorithm Of Haze Image Clearness And Its DSP Implementation

Haze, which is caused by scattering of sunlight by water droplets and other medium in atmosphere, led to the decrease of scene image contrast seriously. Haze image clearness technology is widely used in the field of surveillance systems, traffic navigation, remote sensing systems, and military defense systems. Because of its extensive application value, the haze image clearness technology has been one of the popular research topic in the field of machine vision and image processing.After making a systematic introduction of image enhancement and image recover technology, this paper focus on the issue of haze removal.To overcome the defects of the existing dehazing algorithms, such as poor real-time performance, bad dehaze result in sky area and darken dehaze image, a real-time image haze removal algorithm was proposed in this paper. Firstly, dark channel prior was used to estimate the rough transmission map t(x)?. Secondly, the method of optimized guided filter was adopted to refine the down sampling t(x)?,which was contributed to real-time processing for higher resolution image. Thirdly, correcting the up sampling refine transmission map to obtain the final transmission map t(x), which could overcome the defect of bad effect in sky area. Finally, the clear image was got by adaptive brightness adjustment with color restoration. The complexity of the algorithm is only a linear function of the number of input image pixels, which brings a very fast implementation. For the image which resolution is 600×400,the processing time is 80 ms. The experiment results show that the proposed method not only can significantly improve the contrast and color of haze image with strong robustness, but also the quality and the efficiency is superior to the latest comparison algorithms.On the other hand, the proposed algorithm was implemented on the TI DM642. we completed the real-time video acquisition,sharpness processing and display. This technology can be widely used in traffic safety, video monitoring and so on.