Homomorphic Filtering for Image Processing

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Resource Overview

Applying homomorphic filtering to images followed by local histogram equalization can achieve blur enhancement effects, suitable for applications such as thin cloud removal in remote sensing images. However, this approach requires further refinement and research for optimal results.

Detailed Documentation

Performing homomorphic filtering combined with local histogram equalization on images can produce certain blur enhancement effects. This method finds applications in areas like thin cloud removal for remote sensing imagery. The technique operates by first applying homomorphic filtering to separate illumination and reflectance components in the frequency domain, followed by localized histogram equalization to enhance contrast in specific regions. Implementation typically involves using Fourier transforms for frequency domain processing and adaptive histogram equalization algorithms for local enhancement. However, this approach is not yet fully optimized and requires additional improvements and research to achieve better performance across various image types and conditions.

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