A model of noise reduction using Gabor Kuwahara filter

Noise analysis of the image is the most important part in image processing. A filter is designed to improve the Kuwahara filter to reducing the noise. The Proposed Gabor Kuwahara filter is efficient to reduce the noise without losing the information on edges, before the preparation of the images for segmentation and other image processing techniques. This proposed noise reduction model is automated algorithm incorporated with Gabor transformation. The proposed model results the filtered image without blurring the edges and provides fine quality of images by reducing noise. The experimental results of MSE (Mean Square Error) and SSIM (Structural Similarity Index Measure) using the proposed model is compared with other state-of-art noise reduction method and provides many promising results.