I need some matlab codes for image enhancement using following methods like HE, GHE, BBHE, DSIHE, RMSHE, MMBEBHE, SWHE etc.
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Threads: 61
Joined: Oct 2014
Improvement is the method of improving the capacity of a stored digital electronic image. The main purpose of image enhancement is to process an image and modify the attributes of the given image to make it more suitable than the original image for the particular application. Histogram equalization is the most active and simple method to improve image quality. Histogram equalization (HE), a simple contrast method (CE), tends to show an excessive increase and gives unnatural artifacts in high-peaking images in histograms. Histogram-based EC methods have been proposed to overcome the drawback of HE, however, they do not always give good improvement results. In this letter, a method based on histogram based on the preservation of the locality is proposed.
The proposed method is formulated as an optimization problem to conserve localities of the histogram to perform the CE image. The preservation property of the locality makes the histogram shape of the improved image similar to that of the original image. The experimental results show that the method based on the proposed histogram gives output images with graceful EC in which the existing methods give unnatural results. Improving the image can be used to improve the visual appearance of the image. To improve contrast, the histogram equalization technique is used. Histogram equalization is used to preserve the best brightness of the image. We have studied several histogram equalization techniques such as Brightness Preservation Bi-Histogram Equalization, Dualistic Sub-Image Histogram Equalization, Minimal Brightness Equivalence of Media Brightness, Separate Recursive Media Histogram Equation, Histogram Equalization Equalization Preservation, Preservation Brightness Dynamic Histogram EQ are various histogram equalization techniques. Minimum half-brightness error Bi-Histogram EQ is better than other techniques for preserving image brightness as this technique can be modified and provides enhanced images with better image resolution.
Posts: 14,118
Threads: 61
Joined: Oct 2014
Improvement is the method of improving the capacity of a stored digital electronic image. The main purpose of image enhancement is to process an image and modify the attributes of the given image to make it more suitable than the original image for the particular application. Histogram equalization is the most active and simple method to improve image quality. Histogram equalization (HE), a simple contrast method (CE), tends to show an excessive increase and gives unnatural artifacts in high-peaking images in histograms. Histogram-based EC methods have been proposed to overcome the drawback of HE, however, they do not always give good improvement results. In this letter, a method based on histogram based on the preservation of the locality is proposed.
The proposed method is formulated as an optimization problem to conserve localities of the histogram to perform the CE image. The preservation property of the locality makes the histogram shape of the improved image similar to that of the original image. The experimental results show that the method based on the proposed histogram gives output images with graceful EC in which the existing methods give unnatural results. Improving the image can be used to improve the visual appearance of the image. To improve contrast, the histogram equalization technique is used. Histogram equalization is used to preserve the best brightness of the image. We have studied several histogram equalization techniques such as Brightness Preservation Bi-Histogram Equalization, Dualistic Sub-Image Histogram Equalization, Minimal Brightness Equivalence of Media Brightness, Separate Recursive Media Histogram Equation, Histogram Equalization Equalization Preservation, Preservation Brightness Dynamic Histogram EQ are various histogram equalization techniques. Minimum half-brightness error Bi-Histogram EQ is better than other techniques for preserving image brightness as this technique can be modified and provides enhanced images with better image resolution.