So, first of all, notice that it's pretty certain that the for the DCT coefficient that defines the constant intensity offset ("DC component", an EE would say), the highest quantization level was chosen.Ĭonversely, at least for most higher-frequency components in the 8x8 blocks, quantization error energy is higher. This results in different DCT coefficients being omitted, saved with fewer or more bits.Īs shown in the other answer, averaging on the reconstructed RGB image is a bad idea, since the random noise must lead to you basically seeing an effect of the IDCT of the quantization matrix in each block – meh. A quantization matrix is chosen according to pick a quality/compression trade-off.The original-resolution Y', and the reduced-resolution C b and C r images are split into 8x8 pixel blocks separately.The C b/r channels are low-pass filtered and downsampled.The resulting R'G'B' pixel data, is converted to the Y'C bC r colorspace, meaning you convert the threedimensional red,green,blue signal to the threedimensional brightness,Blue-difference,Red-difference signal.Sadly, this also makes our quantization noise problem harder.
That way, you don't get "pitch black" everywhere for dark images. That is a nonlinear operation, "pushing together" high values and stretching the lower values. Gamma correction is applied to the RGB image first.The second problem now is due to how the JPEG compression works in your camera: The first point is something we cannot really change per se your averaging approach surely is a good one. problems to average things out due to JPEG compression.
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