Adaptive histogram equalization and its variations
Computer Vision, Graphics, and Image Processing
Digital Image Processing
Contrast enhancement using brightness preserving bi-histogram equalization
IEEE Transactions on Consumer Electronics
IEEE Transactions on Consumer Electronics
Minimum mean brightness error bi-histogram equalization in contrast enhancement
IEEE Transactions on Consumer Electronics
Brightness Preserving Dynamic Histogram Equalization for Image Contrast Enhancement
IEEE Transactions on Consumer Electronics
Bi-histogram equalization with a plateau limit for digital image enhancement
IEEE Transactions on Consumer Electronics
Adaptive contrast enhancement methods with brightness preserving
IEEE Transactions on Consumer Electronics
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Among all applications to monitor the safety and security of working environments, surveillance systems that use computer vision are the most efficient and intuitive in the manufacturing industry. This paper introduces a new technique of contrast enhancement for surveillance systems using computer vision. The histogram equalization method is a common and widespread image enhancement method which maximizes the contrast of the image. This contrast enhancement method usually improves the quality of images, but it can suffer from visual deterioration caused by excessive histogram modification. To overcome the limitations of conventional contrast enhancement methods, this paper introduces a new multi-local histogram transformation method for surveillance systems. This technique is based on the local histograms, which are separated from the overall histogram of the image, and the contrast of the image can be enhanced through two major processes: range reassignment of local histograms and local histogram equalization. The multi-local histogram transformation in this paper enhances the contrast of images, preventing excessive compression and extension of image histograms. The performance of the suggested contrast enhancement method is verified by the experiments in four different environments.