Image enhancement is one of the challenging but crucial methods that is employed in image processing technology for enhancing the visual appearance of images. This paper presents an effective and efficient image enhancement model in which Non Local mean (NLM) filter is used along with Minimum Mean Brightness Error Bi-Histogram Equalization (MMBEBHE) and Brightness Preserving Dynamic Fuzzy Histogram Equalization (BPDFHE) techniques. The primary objective of the proposed image enhancement model is to enhance the quality of images by reducing the noise effect in them. To do so, we have selected four different images of Barbara, camera, Lena and Hand whose quality is increased and analyzed on three different noise levels of 15, 20 and 25 respectively. Here, we have used NLM filter which is an advanced filtration technique for denoising the images. Also, MMBEBHE and BPDFHE techniques have been implemented for enhancing the quality of images on different noise levels. The efficiency and usefulness of proposed image enhancement model is examined and validated in MATLAB software under Mean Square Error (MSE) and Peak to Signal Ratio (PSNR) values.
Keywords
Image enhancement, Histogram, Median Filters, NLM, MMBEBHE, BPDFHE
