When performing block-based
discrete cosine transform (DCT)
Block boundary artifacts At low bit rates, any
lossy block-based coding scheme introduces visible artifacts in pixel blocks and at block boundaries. These boundaries can be transform block boundaries, prediction block boundaries, or both, and may coincide with
macroblock boundaries. The term
macroblocking is commonly used regardless of the artifact's cause. Other names include blocking, tiling, mosaicing, pixelating, quilting, and checkerboarding. Block-artifacts are a result of the very principle of
block transform coding. The transform (for example the discrete cosine transform) is applied to a block of pixels, and to achieve lossy compression, the transform coefficients of each block are
quantized. The lower the bit rate, the more coarsely the coefficients are represented and the more coefficients are quantized to zero. Statistically, images have more low-
frequency than high-frequency content, so it is the low-frequency content that remains after quantization, which results in blurry, low-resolution blocks. In the most extreme case only the DC-coefficient, that is the coefficient which represents the average color of a block, is retained, and the transform block is only a single color after reconstruction. Because this quantization process is applied individually in each block, neighboring blocks quantize coefficients differently. This leads to discontinuities at the block boundaries. These are most visible in flat areas, where there is little detail to mask the effect.
Image artifact reduction Various approaches have been proposed to reduce image compression effects, but to use standardized compression/decompression techniques and retain the benefits of compression (for instance, lower transmission and storage costs), many of these methods focus on "post-processing"—that is, processing images when received or viewed. No post-processing technique has been shown to improve image quality in all cases; consequently, none has garnered widespread acceptance, though some have been implemented and are in use in proprietary systems. Many photo editing programs, for instance, have proprietary JPEG artifact reduction algorithms built-in. Consumer equipment often calls this post-processing
MPEG noise reduction. Boundary artifact in JPEG can be turned into more pleasing "grains" not unlike those in high ISO photographic films. Instead of just multiplying the quantized coefficients with the quantisation step pertaining to the 2D-frequency, intelligent noise in the form of a random number in the interval can be added to the dequantized coefficient. This method can be added as an integral part to JPEG decompressors working on the trillions of existing and future JPEG images. As such it is not a "post-processing" technique. The ringing issue can be reduced at encode time by overshooting the DCT values, clamping the rings away. Posterization generally only happens at low quality, when the DC values are given too little importance. Tuning the quantization table helps. == Video ==