Open AccessIMAGE DENOISING USING WAVELET AND SHEARLET TRANSFORM
Author(s) -
Bharath Kumar S,
Kavyashree,
Ananth V Naik,
Kavyashree C.L,
Gayathri K.M
Publication year - 2017
Publication title -
international journal of research - granthaalayah
Language(s) - English
Resource type - Journals
eISSN - 2394-3629
pISSN - 2350-0530
DOI - 10.29121/granthaalayah.v5.i4raceee.2017.3316
Subject(s) - computer science , artificial intelligence , wavelet transform , wavelet , noise reduction , speckle noise , video denoising , computer vision , shearlet , noise (video) , image restoration , non local means , image processing , matlab , image (mathematics) , gaussian noise , pattern recognition (psychology) , image denoising , video processing , video tracking , multiview video coding , operating system
Image plays an important role in this present technological world which further leads to progress in multimedia communication, various research field related to image processing, etc. The images are corrupted due to various noises which occur in nature and poor performance of electronic devices. The various types of noise patterns observed in the image are Gaussian, salt and pepper, speckle etc. due to which the image is attenuated or amplified. The main challenge lies in removing these noises. We use various denoising techniques in removal of noise in order to retrieve the original information from the image. Wavelet transforms are one of the denoising algorithms used as conventional methods. This algorithm is used to capture the image along different directions in limited manner which becomes the main disadvantage of using this algorithm. In this work we propose a technique by integrating Wavelet and Shearlet transform which effectively removes the noise to the maximum extent and restores the image by edge detection which can be identified. The simulation is done on synthetic image and shows improvement with existing methods. The algorithm is simulated in MATLAB 2016b.