A Combinational Histogram Equalization Related to Contrast Image Enhancement

This is the authors' abstract. We don't add key points for this paper.

The limitation to the most commonly used histogram equalization (HE) technique is the inconsideration of the neighbourhood info near each pixel for contrast enhancement. This gives rise to noise in the output image. Image enhancement tools are often classified into point operations and spatial operations. To overcome this effect, a combinational images of histogram equalization (CHE) based technique is suggested. The focus is to utilize the information among each pixel and its neighbours, which improves the contrast of an image. This method is used in an only two-dimensional images. This histogram is using the original image and its intermediate image. Further, it does not require a target uniform distribution for generating the output. The 2-D cumulative distribution function (CDF) is utilized as a mapping function to get the output pixel intensity. The experimental analysis indicates that the procedure produces better results than the HE based contrast enhancement algorithms. More significantly, it produces the best results even for images having a narrow dynamic range. The implementation simplicity of the proposed algorithm may attract researchers to explore the idea for new applications in image processing.