quantization matrix is designed to provide more resolution to more perceivable frequency components over less perceivable components (usually lower frequencies over high frequencies) in addition to transforming as many components to 0, which can be encoded with greatest efficiency. Many video encoders (such as DivX, Xvid, and 3ivx) and compression standards (such as MPEG-2 and H.264/AVC) allow custom matrices to be used. The extent of the reduction may be varied by changing the quantizer scale code, taking up much less bandwidth than a full quantizer matrix. This is an example of DCT coefficient matrix: A common quantization matrix is: Dividing the DCT coefficient matrix element-wise with this quantization matrix, and rounding to integers results in: For example, using −415 (the DC coefficient) and rounding to the nearest integer Typically this process will result in matrices with values primarily in the upper left (low frequency) corner. By using a zig-zag ordering to group the non-zero entries and run length encoding, the quantized matrix can be much more efficiently stored than the non-quantized version. See also Image segmentation Image-based meshing Range segmentation References Lossy compression algorithms Image compression