Optimized Edge Detection Using Fuzzy and Wavelet De-Blurred Image Threshold

In image processing edge detection is an essential topic. We propose a new method for a simple edge detection and fast computation using fuzzy logic rule .We compare proposed edge detector to other existing edge detectors such as sobel edge detector, canny edge detector, and prewit edge detector. In addition it also deblurred the images efficiently and effectively. We present a new image deblurred method: wavelet image threshold de blurring. In these wavelet coefficients of an image that related to an image’s edges are primarily detected by wavelet edge detection. The detected wavelet coefficients will then be saving from de blurring; therefore we set a de blurring thresholds based on the blurring variances without disturbing of image edge. Proposed work can save image’s edges from noise and step up the PSNR up to 1-2db.If we combine both image de blurring and edge detection of image. We can get rid of commonly used de blurred methods and also can detect image effectively &efficiently.