Research on image enhancement technology based on dynamic histogram transformation under low illumination conditions

Low-illumination images have poor image quality due to characteristics such as insufficient brightness, low contrast, and noise interference, which brings difficulties to subsequent image processing. As an effective image preprocessing technique, histogram transformation can adjust the distribution of gray levels in an image, thereby improving the contrast, brightness, and clarity of the image. The characteristic presented by low-illumination images on the gray histogram is that pixels are concentrated in one or several gray ranges. The small difference between the pixel values of the main target's gray level and those of the adjacent gray levels will result in indistinct features of the main target. In response to the above problems, this paper proposes an image enhancement technique based on dynamic histogram transformation, aiming to enhance the contrast of the main (or background) target in the image. Different transformation ranges and shape parameters will lead to different contrast enhancement effects. The simulation results show that by changing the shape of the peak in the histogram, the contrast of the main target in the image is strengthened and the details become more prominent.