A Review on Extracting Deblur Image Using Fuzzy Logic Approach From Impulse Noise
The image processing is very crucial field of research in which we can get the complete and detailed information about any image. One of the main issues in our research field is to get the quality of an image. So we will try to propose an advanced algorithm to enhance the quality of an image by removing noise. Deblurring techniques are basically used to sharp an image using different methods & parameters so that we can the abundant amount of knowledge. As we know there are various types of noises occurred in an image and like salt & pepper noise, additive white Gaussian noise, flicker noise, shot noise and many more. To compensate these noises there are various types of technique like algorithm, filtering concept, fuzzy logic approach and much more. Every technique is suitable for a particular noise and we cannot apply randomly to remove a particular noise. In last few years there is lot of development and attentions in area of blur detection techniques. The Blur detection techniques are very helpful in real life application and are used in image segmentation, image restoration, and image enhancement. Blur detection techniques are used to remove the blur from a blurred region of an image which is due to defocus of a camera or motion of an object
Published by: Preeti, Sachin Suryan
Author: Preeti
Paper ID: V3I3-1307
Paper Status: published
Published: May 11, 2017
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