3 ms·
The word is "blur." Low-pass filtering is blurring. Is blurring good for compression? I don't know what that means. If the image size (not the file size) is he
by itishappy 3y ago
The word is "blur." Low-pass filtering is blurring.
Is blurring good for compression? I don't know what that means. If the image size (not the file size) is held constant, a blurry image and a clear image take up exactly the same amount space in memory.
Blurring is bad for quality. Our vision is sensitive to high-frequency stuff, and low-pass filtering is by definition the indiscriminate removal of high-frequency information. Most compression schemes are smarter about the information they filter.
- acuozzo 3y ago> Is blurring good for compression? I don't know what that means. Consider lossless RLE compression schemes. In this case, would data with low or high variance compress better? Now consider RLE against sets of DCT coefficients. See where this is going? In general, having lower variance in your data results in better compression. > Our vision is sensitive to high-frequency stuff Which is exactly why we pick up HF noise so well! Post-processing houses are very often presented with the challenge of choosing just the right filter chain to maximize fidelity under size constraint(s). > low-pass filtering is by definition the indiscriminate removal of high-frequency information It's trivial to perform edge detection and build a mask to retain the most visually-meaningful high frequency data.