ISSN(Online): 2320-9801 ISSN (Print) : 2320-9798 International Journal of Innovative Research in Computer and Communication Engineering (A High I mpact Factor, Monthly, Peer Reviewed Journal) Website: www.ijircce.com Vol. 6, Issue 3, March 2018 Copyright to IJIRCCE DOI: 10.15680/IJIRCCE.2018.0603138 2498 Review of Different Techniques for Image Denoising Akram Abdul_Maujood Dawood 1 , Muhanad Faris Saleh 2 Lecturer, Department of Computer Engineering, University of Mosul, Mosul, Iraq 1 Assistant Lecturer, Department of Computer Engineering, University of Mosul, Mosul, Iraq 2 ABSTRACT: In this paper, different techniques of image denoising that deal with removing or reducing different types of noise from a distorted image, are reviewed. Nowadays, the tendency is to speeding-up the applied algorithms to overcome the processing delay of the classical iterative methods (having 50 to 100 iterations or even more). This is apparent when dealing with high levels of noise. Since it is necessary to have idea about the noise present in the image to select the appropriate denoising algorithm, this paper state first a brief description of noise and its different types including Gaussian, salt and pepper and speckle noise. Image denoising techniques are then presented, namely; classical techniques (such as mean, order and adaptive filters) and transform-based techniques (such as wavelet and contourlet transforms). KEYWORDS: image restoration; classical filters; Gaussian noise; impulse noise, salt and pepper noise, speckle noise, mean filters, order filters, adaptive filters, wavelet transform, contourlet transforms. I. INTRODUCTION The large proliferation of digital cameras and the widespread use of the Internet have produced a huge number of digital images that were generally taken by different unknown imaging devices under undefined lighting conditions, which made balancing and restoring the properties of the real scene necessary. The quality of these images is often improved by the digital processing of the image. The most important treatment methods are image denoising of noisy images. Denoising is more significant than any other tasks in image processing [1]. Reserving the details of an image and removing the random noise as far as possible is the goal of image denoising approaches. Noise removal is essential in digital imaging applications in order to enhance and recover fine details that are hidden in the data. In many occasions, noise in digital images is found to be additive in nature with uniform power in the whole bandwidth and with Gaussian probability distribution. Such a noise is referred to as Additive White Gaussian Noise (AWGN). It is difficult to Suppress AWGN since it corrupts almost all pixels in an image. In denoising there is always a trade off between noise suppression and preserving actual image discontinuities. To remove noise without excessive smoothing of important details, a denoising technique needs to be spatially adaptive [2].And there is another type of noise called Speckle noise which is considered multiplicative noise and it is one of the most complex abnormalities that appear in the Synthetic Aperture Radar Sensors (SAR), Ultrasonic systems and laser systems. There is many techniques are used to restore or denoise image like classical filters, discrete wavelet transform and contourlet transform. Hence, it is necessary to have knowledge about the noise present in the image so as to select the appropriate denoising algorithm. The paper is organized as follows: Section II contains RELATED WORK. Section III includes the Types of Noise and review of the different image denoising techniques. Finally, section IV concludes this paper.