Podcast #128: We chat with Kent C Dodds about why he loves React and discuss what life was like in the dark days before Git. Listen now.

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Looking at this page it looks like the Kawase kernel is just a way of implementing a linear kernel quickly, but in a way that constrains the kernel somewhat. This means that you could make such an algorithm. Either choose a set of spreads and adjust their weights (if that is possible) for a best fit, or search a number of possible spreads (with the best ...


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A simple way to calculate contrast is by computing the standard deviation of the greyed image pixel intensities.


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My guess would be that making an image sharper translates into a spectrum that have more high frequency and less low frequency: i.e. the weighted median frequency would increase. Now you can define a relative measure of image sharpness. To get an absolute measure of image sharpness, you need to define what is maximum and minimum sharpness, and find a way to ...


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Some references on image sharpness metrics: Encoding Visual Sensitivity by MaxPol Convolution Filters for Image Sharpness Assessment, IEEE Transactions on Image Processing, 2019 A Fast Approach for No-Reference Image Sharpness Assessment Based on Maximum Local Variation, IEEE Signal Processing Letters, 2014 Image Sharpness Assessment Based on Local Phase ...


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