(IJIRSE) International Journal of Innovative Research in Science & Engineering ISSN (Online) 2347-3207 IJIRSE/2016/Vol 4. Iss. 8/ Page 122 Implementation of Image Restoration Techniques in MATLAB Jitendra Suthar 1 , Rajendra Purohit 2 Research Scholar 1 ,Associate Professor 2 Department of Computer Science, JIET, Jodhpur Abstract:- Processing of digital images with the help of digital computers known as Digital Image Processing. One of the most applicable areas in Image Processing methods is to enhance the pictorial information for human perception. Image restoration is a method to clearing the degraded image to obtain the original image. For years researchers have been working in developing new techniques that can restore the original image from degraded image. The aim of this paper is to demonstrate the implementation of different types of techniques for image Restorations in MATLAB. MATLAB is very powerful tool for image processing because it support all types of image format and conversion between them. It also support all types of datatypes. Index terms: Blur, MATLAB, Image processing tool, Deblurring, PSF and Image Restoration. I. INTRODUCTION Image restoration is an old problem in the field of image processing, one that continues to accumulate attention from academics and businesses alike [8]. Its application areas are observed in many different real-world problems and work as an easy way to visualize examples of a larger range of inverse problems in many fields [1]. Image Processing Tool provides a complete set of standard algorithms and graphical tools for image processing, visualization, analysis and algorithm development. It able to restore noisy or distorted images, analyze shapes and textures in image, enhance the viewing quality of images, extract desired features from image and also register two images. Image Processing Tool provide facility to scientists and engineers in areas such as biometrics, semiconductor testing, surveillance, gene expression, microscopy, remote sensing, image sensor design, materials science and colour science.[2] II. INTRODUCTION TO MATLAB Most functions in Image Processing Tool are written in the open source MATLAB language, giving us the facility to inspect the algorithms, create our own custom functions and modify the source code. A. Key Feature  Image smoothing, image sharpness, image enhancement, deblurring, contrast enhancement and filters design.  Image analysis, including feature detection, segmentation, morphology and measurement.  Image registration and spatial transformations.  Image transforms, including, DCT, DWT, FFT, IFFT, Radon and fan-beam projection.  DICOM (Digital Imaging and Communications in Medicine) file import and export. B. Image Formats in MATLAB There is lossy and lossless algorithm. Lossless algorithms will reduces size without degrading, quality of picture so it cannot compress file to a very small size for better compression. Lossy method allows reduces image size but it will degrade the quality of picture. It able to analyze, visualize and process these images in different data structure (data types), including floating point (single precision and double precision) representation and signed or unsigned 8 bit, 16 bit and 32 bit integer values. There are many ways to process an image in MATLAB