Color image restoration based on camera microscanning José L. López-Martínez, a* Vitaly Kober, b,c** Manuel Escalante-Torres a a Mathematics School UADY, Mérida, Yuc. 97110, Mexico b Department of Computer Science, CICESE, Ensenada, B.C. 22860, Mexico c Department of Mathematics, Chelyabinsk State University, Russian Federation ABSTRACT In this work, we propose a method to restore color images from a set of degraded color images obtained with a microscanning imaging system. Using the set of observed images, image restoration is carried out by solving a system of equations that is derived from optimization of an objective function. Since the proposed method possesses a high computational complexity, a fast algorithm is developed. Experimental and computer simulation results obtained with the proposed method are analyzed in terms of restoration accuracy and tolerance to additive input noise. Keywords: Color image restoration, image processing, microscanning 1. INTRODUCTION Image restoration is a very popular area of image processing. 1,2 Basically, image restoration is the process of signal recovery or reducing degradations owing to capturing process. 3,4 These degradations include blurring, aliasing, additive interference, multiplicative interference and sensor’s noise. The additive interference (bias) is present in focal-plane array sensors (FPA) that are frequently used in visible-light and infrared imaging systems. 5,6 This bias is a spatial nonuniformity, which is owing to variations in the photo-responses of individual detectors of the array. 7 The multiplicative interference can occurs due to non-uniform illumination. 8 Microscanning is a process of generating multiples frames from a common scene by shifting either the scene or image- acquisition system. 9,10 Recently, a blind adaptive method based on camera microscanning were proposed for restoration of gray-scale images degraded with multiplicative interference, additive interference and sensor’s noise. 11,12 In this paper we present a method to restore color images from a set of degraded color images obtained with a microscanning imaging system. First, we use microscanning to obtain a set of observed degraded color images of the same scene with a controlled shift between the scene and camera. Next, we process each component of color image (RGB color model) with the blind adaptive algorithm. Finally, we form a color image from the individually processed components. It is assumed that the degradation function is unknown. 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. The paper is organized as follows. In section 2, the proposed method and fast algorithm are presented. In section 3, we illustrate the performance of the method with the help of computer simulation. Section 4 summarizes our conclusions. 2. RESTORATION METHOD Let us introduce some notation and definition. Let { } L j L i s S j i , , 1 ; , , 1 , , K K = = = be an observed scene, { } L j L i f F j i , , 1 ; , , 1 , , K K = = = be an original image, { } L j L i a A j i , , 1 ; , , 1 , , K K = = = be an additive interference, _________________________________ Further author information: *J. L-M. (correspondence): e-mail: jlopezm@uady.mx **V. K.: email: vkober@cicese.mx Applications of Digital Image Processing XXXVII, edited by Andrew G. Tescher, Proc. of SPIE Vol. 9217, 921707 © 2014 SPIE · CCC code: 0277-786X/14/$18 · doi: 10.1117/12.2061443 Proc. of SPIE Vol. 9217 921707-1 Downloaded From: http://proceedings.spiedigitallibrary.org/ on 09/25/2014 Terms of Use: http://spiedl.org/terms