Degradation of images is one of the major problems in image processing. Blur in images is an unwanted reduction in bandwidth which degrades the image quality and it is difficult to avoid. Blur occur due to atmospheric turbulence as well as improper setting of camera. Along with blur effects, noise also corrupts the captured image. Restoration of image is a technique to get rid of the blur from the degraded image and recover the original image. Blur can be of various types like Gaussian blur, motion blur etc. Now a day's there are various different techniques and methods have been proposed to deblur a degraded image. For specific types of blur there are specific methods to remove it. Image restoration has applications in various different-different fields like medical imaging, forensic science, and astronomy. In this paper, we will discuss various image deblurring techniques and their analysis of performance.
In computer science, mutual exclusion (MUTEX) refers to a way of making sure that if one process is using shared modifiable data or resources then the other processes will be excluded from doing the same thing at the same time. A number of mutual exclusion algorithms are available in the literature, with different performance metrics and with different techniques. The Selection for a "good" mutual exclusion algorithm is a key point. These mutual exclusion algorithms can be broadly classified into token and non-token based algorithm. This paper surveys the algorithms which have been reported in the literature for Mutual exclusion in distributed systems and their comparison.
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