[rer0tsaz]

Let me share my experience with chroma upsampling and smooth jpeg decoding.

At first, I optimized each channel, then upsampled the chroma channels using replication. This works terribly as you can see in the article.

So then I changed to linear interpolation. Briefly:

    +---+---+
    a x b y c
    +---+---+

We know the values in a and c but not b. The distance from x to a is half a pixel and the distance from x to c is one and a half pixel. Then linear interpolation gives x = a + (c - a) * (1/2 - 0) / (2 - 0) = 3/4 a + 1/4 c.

This worked decently, but it still showed fringes around sharper edges. I considered using more complicated upsampling methods like Lanczos or Mitchell, but instead went with optimizing a full size image with constraints on the downsampled image. By avoiding upsampling I got my optimized high resolution image for each channel.

But there were still fringes! As it turns out, just because each channel was optimized seperately doesn't mean that the image as a whole is optimized. So I switched to optimizing the three YCbCr channels together, not looking at the differences abs(x_{i+1} - x_i) but looking at the differences sqrt((Y_{i+1} - Y_i)^2 + (Cb_{i+1} - Cb_i)^2 + (Cr_{i+1} - Cr_i)^2). This actually eliminated the fringes.

The final result is https://github.com/victorvde/jpeg2png