Abstract
This paper explores the possibility of utilizing histogram equalization on images captured in poor lighting conditions in order to expand their histogram dynamic range, enhancing their contrast and effectively provide night vision for such images. Then, some drawbacks of standard histogram equalization for dark images, caused mainly due to the clustering of pixels around the lowest intensities are exposed, and Enhanced Intensity Weighted Histogram Equalization is presented as a solution to obtain more realistic night vision images by incorporating the normalized weight of each pixel intensity into the calculations and spreading the histogram values to fill in the gaps, reducing noisy high frequency changes. This technology can be applied to new capture devices that detect the lack of illumination and engage Enhanced Intensity Weighted Histogram Equalization to provide low light capture, useful for surveillance, driving, medical imaging, and even space exploration.
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