  In video coding, it is expected that the encoder could adaptively select the
encoding parameters (e.g., quantization parameter) to optimize the bit
allocation to different sources under the given constraint. However, in hybrid
video coding, the dependency between sources brings high complexity for the bit
allocation optimization, especially in the block-level, and existing
optimization methods mostly focus on frame-level bit allocation. In this paper,
we propose a macroblock (MB) level bit allocation method based on the minimum
maximum (MINMAX) criterion, which has acceptable encoding complexity for
offline applications. An iterative-based algorithm, namely maximum distortion
descend (MDD), is developed to reduce quality fluctuation among MBs within a
frame, where the Structure SIMilarity (SSIM) index is used to measure the
perceptual distortion of MBs. Our extensive experimental results on benchmark
video sequences show that the proposed method can greatly enhance the encoding
performance in terms of both bits saving and perceptual quality improvement.
