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Authors
Affiliations
1 Computer Science Engineering Department,
GZS-PTU Campus, Bathinda, IN
Source
Research Cell: An International Journal of Engineering Sciences, Vol 12 (2014), Pagination: 13-17
Abstract
Images are used in a variety of fields for image analysis and image understanding. Digital images are usually degraded by various types of noise due to sensor problems, weather problems and so on. In this paper, we represent a new technique for removing noise from images. Image enhancement is based on the multi scale singularity detection with an adaptive threshold whose value is calculated with different ways. Wavelet transforms are used because of their inherent property that they are redundant and shift invariant. In different scales of an image intensity changes occurs, so there is need of optimal detection that requires the use of operators of different sizes. Therefore, a vision filter must be a differential operator, and it must be capable of being tuned to act at any desired scale and the wavelets are ideal for this. Principle objective of Image enhancement and denoising is to process an image so that result is more suitable than the original image for specific application. This paper will provide an overview of underlying concepts commonly used for image enhancement.
Keywords
Spatial Domain, Frequency Domain, Discrete Wavelet Transforms (DWT), Daubechies Wavelets, Neuro-Fuzzy Logic, Peak Signal to Noise Ratio(PSNR) and Mean Square Error(MSE).
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