MATLAB Implementation of Image Sharpness Assessment
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Resource Overview
Image sharpness evaluation using standard deviation, spatial frequency threshold, entropy, and Brenner's measure with MATLAB code implementation
Detailed Documentation
Image sharpness assessment is measured through a series of metrics, including standard deviation, spatial frequency threshold, entropy, and Brenner's measure. These metrics evaluate image sharpness from different perspectives, providing comprehensive assessment results.
Implementation in MATLAB typically involves:
- Calculating standard deviation using std2() function for pixel intensity variations
- Computing spatial frequency threshold through Fourier transform analysis with fft2()
- Measuring image entropy using entropy() function for information content quantification
- Implementing Brenner's gradient measure by convolving with gradient filters
The algorithm processes each metric independently and combines results for overall sharpness evaluation. Key functions include image preprocessing, metric calculation, and result normalization for comparative analysis across different images.
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