Abstract
Visual information transfer in the form of digital images becomes a vast method of communication in the modern scenario, but the image obtained after transmission is many a times corrupted with noise. The received image requires some processing before it can be used. Image denoising includes the manipulation of the image data to produce a visually high-quality image. In this paper a review of some existing denoising algorithms, such as filtering approach; wavelet-based approach and their comparative study has been done. Different noise models including additive and multiplicative types are discussed. It includes Gaussian noise, salt and pepper noise, speckle noise and Brownian noise. Selection of the denoising algorithm is application dependent. Hence, it is necessary to have knowledge about the noise present in the image so that one can opt the appropriate denoising algorithm. The filtering approach seems to be a better choice when the image is corrupted with salt and pepper noise. Whereas, wavelet-based techniques are suited for more detailing. In this paper denoising techniques for AWGN corrupted image has been mainly focused.
Recommended Citation
Parihar, Sumit Singh and Khaparkar, Shailesh
(2024)
"Filter-based Denoising Methods for AWGN corrupted images,"
American Journal of Science & Engineering (AJSE): Vol. 2:
Iss.
1, Article 2.
Available at:
https://research.smartsociety.org/ajse/vol2/iss1/2