JPEG 压缩图像时用 8x8 区块处理图像, 而不是对整个图像应用分解的 Cosine 变换?
8X8是在用其他尺寸进行多次试验后选定的。
The conclusions of experiments are: 1. Any matrices of sizes greater than 8 X 8 are harder to do mathematical operations (like transforms etc..) or not supported by hardware or take longer time. 2. Any matrices of sizes less than 8 X 8 dont have enough information to continue along with the pipeline. It results in bad quality of the compressed image.
因为这样需要“ 永远” 才能解码。 我现在不完全记得了, 但我认为你至少需要与区块中像素一样多的系数。 如果您将整幅图像编码成一个块, 我认为你需要, 对于每个像素, 通过所有 DCT 系数循环。
我不太擅长大O计算 但我猜复杂的是O("永远")
现代视频编码器 我想他们已经开始使用 16x16区块
一个良好理由是图像(或至少是人类喜欢看的那种图像)在当地具有高度的信息相关性,但并非全球范围。
每个相对平滑的皮肤片段, 或一片天空或草地或墙壁最终会以尖锐的边缘结束, 并被完全不同的东西所取代。 这意味着您仍然需要一个高频截断, 才能充分代表图像, 而不是仅仅模糊图像 。
现在,因为Fourier式的变异就像DCT“jumble” 所有和平信息, 你也无法丢弃任何中间系数, 或高频组件“你不喜欢” 。
当然,还有其他方法可以试图丢弃视觉噪音,同时通过仅在需要时才保留高频组件来重建边缘,或者以更精细的层次对图像进行一些迭接重建。 您可能想要查看空间尺度的显示和波浪变换。
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