Brother M's research is quite thorough.
On this basis, I am willing to share my views with everyone.
First of all, what cannot be ignored is that this file is a GIF file.
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GIF is a compression method based on mathematical formulas.
Its principle is to describe discrete values with continuous functions.
Then, after compression, the file will have a loss of image quality. These losses must be reduced to the range that can be observed by the naked eye (according to the compression ratio) or to an acceptable range.
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For us, these files will have a loss of image quality after compression. In GIF, the image loss means the smearing of pixels, that is, blurring, but these only consider the positive display effect, so the situation where there is an approximate white instead of white on the image, and a similar black but actually another color. These are because when displaying positively, due to being extremely similar to the adjacent colors, the human eye cannot detect it (the compression ratio is appropriate). But when inverting the color, it completely distinguishes from the foreground color, background color, and transparent color, so there are "hidden" images.
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In fact, such a phenomenon completely exists in other complex images. For example, the two emoticons at the end of this article will have "white" edges when inverting the color, but since we are sure to ignore the noise after inverting the color of complex images. So when such a situation occurs in simple images - especially regular geometric figures (the color smearing generated by the compression algorithm is also regular) - we are very surprised.
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Forgive me for writing the above words in paragraphs, because my old K6-2 computer may be approaching the end of its life, and it frequently freezes

[ Last edited by fdsiuha on 2005-9-5 at 23:20 ]
On this basis, I am willing to share my views with everyone.
First of all, what cannot be ignored is that this file is a GIF file.
-----------------------------------------------------------
GIF is a compression method based on mathematical formulas.
Its principle is to describe discrete values with continuous functions.
Then, after compression, the file will have a loss of image quality. These losses must be reduced to the range that can be observed by the naked eye (according to the compression ratio) or to an acceptable range.
-----------------------------------------------------------
For us, these files will have a loss of image quality after compression. In GIF, the image loss means the smearing of pixels, that is, blurring, but these only consider the positive display effect, so the situation where there is an approximate white instead of white on the image, and a similar black but actually another color. These are because when displaying positively, due to being extremely similar to the adjacent colors, the human eye cannot detect it (the compression ratio is appropriate). But when inverting the color, it completely distinguishes from the foreground color, background color, and transparent color, so there are "hidden" images.
-----------------------------------------------------------
In fact, such a phenomenon completely exists in other complex images. For example, the two emoticons at the end of this article will have "white" edges when inverting the color, but since we are sure to ignore the noise after inverting the color of complex images. So when such a situation occurs in simple images - especially regular geometric figures (the color smearing generated by the compression algorithm is also regular) - we are very surprised.
-----------------------------------------------------------
Forgive me for writing the above words in paragraphs, because my old K6-2 computer may be approaching the end of its life, and it frequently freezes

[ Last edited by fdsiuha on 2005-9-5 at 23:20 ]
欢迎造访DOS的小屋!
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http://risky.ik8.com

