Research Of Local Image Enhancement Algorithm

Image enhancement is one of the most commonly used in image processing technology, which belongs to the to the basic image processing. It is an important of image preprocessing. Paper from local image enhancement processing and local filtering de-noising, the basic algorithm and theory, to enhance the image of local area and common impulse noise image. Aimed at enhancing the image of local area and common impulse noise image. Studied the image enhancement algorithms of the local details and based on gray transform and histogram modification method are compared, and research learning, analyzes the advantages and disadvantages of each. According to the desired range of local mean and local standard deviation choice the darker area to be reinforced, two improved local enhancement algorithms of image. De-noising image processing to one of the most basic of the most widely used technology, its role is to improve the signal to noise ratio desired feature, striking images. In this paper, the common de-noising algorithm has made the further research, an improved median filtering algorithm is proposed, it is a kind of new image de-noising based on noise detection of impulse noise filtering algorithm. Specific content is as follows:1.The algorithm based on local histogram enhanced image research. The local image enhancement algorithm is proposed combining local histogram specification, simple, practical, and enhance the image of local area at the same time to enhance the image contrast. The experimental results show that the algorithm is better than the local image enhancement of commonly used. Enhanced image detail taking into account the contrast of the image.2. Local contrast enhancement algorithm based on histogram statistics. The improved algorithm is proposed based on the local mean and standard deviation of enhancement algorithm. Algorithm of enhancement coefficient adaptive dynamic change with the image of the local mean and local standard deviation. Implementation details of image local darker areas increased, and Because the algorithm is adaptive, the image enhancement is more targeted. Experimental results show that the improved algorithm not only has a better enhancement effect than the common local contrast enhancement algorithm but also can enhance the dark region of the image when the bright region remains unchanged, it is possible to sufficiently enhance the local image more clearly highlight the image detail in the dark areas.3.The image enhancement algorithm local filtering De-noising. I proposed a new impulse noise filtering algorithm based on adaptive median filter in noise inspection, which is improved then before. This algorithm developed the appropriate threshold and removed the impulse noise by using the adaptive median filter. The simulation results show that the algorithm is effective, the ability to maintain image detail and slightly better than the adaptive median filtering.