Image Enhancement in Block Approach
A simple and dynamic wavelet-based algorithm is presented for enhancement of the image sharpness or blurriness of an Image. Some sets of methods are followed here (Decomposition, Sharpness Estimation, and Filtering). It operates by initially decomposing the input image through a multi-level separable DWT. After this, the log-energies of the DWT sub bands are computed. A Scalar Index corresponding to the input image’s sharpness is computed through the weighted average of the computed log-energies. Several Satellite images are taken into consideration and the Scalar Sharpness Index representing the image’s overall sharpness denoted as SSI. This is used as a filtering component and the image is filtered out to give the Sharpened Image. Here along with the Scalar Sharpness Index, a Block based algorithm is presented to determine the local perceived sharpness. The Block Based Scalar Sharpness Index is calculated by taking the RMS of 0.01 of largest value of the filtering parameter which takes the no. of Block Size. This proposed method is the simplest, fastest and accurate comparing to the currently best-performing techniques.
Cite As
Sandeep Mishra (2024). Image Enhancement in Block Approach (https://www.mathworks.com/matlabcentral/fileexchange/45018-image-enhancement-in-block-approach), MATLAB Central File Exchange. Retrieved .
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- Signal Processing > Wavelet Toolbox >
- Image Processing and Computer Vision > Image Processing Toolbox > Image Filtering and Enhancement > Neighborhood and Block Processing >
- Image Processing and Computer Vision > Image Processing Toolbox > Image Filtering and Enhancement > Deblurring >
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Version | Published | Release Notes | |
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1.2.0.0 | If relevant cite this article: Sandeep Mishra, Radhanath Patra, Abanikanta Pattanayak, “Block Based Enhancement of Satellite Images using Sharpness Indexed Filtering”, IOSR Journal of Electronics and Communication Engineering, vol. 8, Nov-Dec, 2013. |
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1.1.0.0 | One Restriction |
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1.0.0.0 |