Fast image restoration algorithm based on camera microscanning

Abstract

Recently, a blind image restoration algorithm based on camera microscanning was proposed. Unfortunately, the computational complexity of the algorithm is very high. In this paper we propose a fast algorithm for image restoration using the information obtained during camera microscanning. First, the captured observed images are decomposed into a pyramidal set of small images. Next, the blind iterative algorithm is applied for restoration of the set of small images. Finally, the resultant output image is constructed from the set of restored small images. Simulation results are presented and discussed. Preliminary results show that the processing time is significantly reduced.

Color image restoration based on camera microscanning

“…So, the computational complexity of the method for restored color images is very high, we proposed a fast color image restoration using pyramidal decomposition based on a fast image restoration for gray-scale images. 13 …”

“…Since computational complexity of the method is very high, we also propose a fast color image restoration using pyramidal decomposition for gray-scale images. 13 With the help of computer simulations we analyze the performance the proposed technique.…”

CWMA: Circular Window Matching Algorithm

“…3. In order to accelerate the proposed algorithm a decomposition technique [14] is exploited. As shown in Fig 4, an image can be decomposed in a set of small images by decimating in each direction depending on a decomposition level L; i. e. when L = 2, the image is divided in 4 similar images that can reconstruct the original image by performing the inverse process, in a similar way, if L = 3 there are 9 images, and so on.…”