The 4×4 approximate discrete cosine transform (DCT) of H.264/AVC [1] makes it difficult to transcode the pre-coded video contents with the previous video coding standards to H.264/AVC in DCT domain. This is due to the difference between 8×8 DCT used previous standards and 4×4 DCT in H.264/AVC. In this paper, we propose an efficient algorithm that converts the quantized 8×8 DCT block of MPEG-2 i...

Transform coding is routinely used for lossy compression of discrete sources with memory. The input signal is divided into N -dimensional vectors, which are transformed by means of a linear mapping. Then, transform coefficients are quantized and entropy coded. In this paper we consider the problem of identifying the transform matrix as well as the quantization step sizes. We study the challengi...

This paper proposes the implementation of context adaptive variable length coder for H.264 video encoder. The implementation is capable of bringing about compression of video sequences as per user specification and is capable of processing high resolution pictures of sizes of up to 1024 x 768 pixels, encoding at a real time frame rate of 25 fps. The variable length coder has been realized using...

In this a paper a quadtree based method is proposed for classifying blocks of samples in image subbands. Classi cation of blocks of subband samples according to their energy and variable bit allocation within the subsequent classes has demonstrated considerable gains in coding e ciency. The gains due to classi cation increase as smaller blocks are used; however, so do the overheads for transmit...

Requantization is one of the tools for bit-rate reduction of pre-encoded video to adapt it to various network bandwidth constraints. Several recent works propose using Lagrangian optimization to find the optimal quantization step, for each coded macro-block, to meet a desired rate at minimum distortion. In this paper we propose to extend the Lagrangian optimization procedure by allowing modific...

Puri and Aravind’s method of macroblock bit count estimation for video rate control is based on the classification of the macroblock data into discrete classes and assigning a unique nonlinear estimate for each class and quantization parameter pair. This method stands apart from other methods in the literature, since the model of the bit count versus the quantization parameter relation, paramet...

Vector quantization-based approaches to speech coding have generated new interest in very low bit rate speech coding, that is, speech coded to bit rates below 1200 bits/sec. To achieve such low bit rates, it is necessary to quantize the pitch and energy parameters at rates below 100 bits/sec. Contour quantization is introduced as a technique in which the contour of a given parameter is normaliz...

Approaching the 1.5329-dB shaping (granular) gain limit in mean-squared error (MSE) quantization of R is important in a number of problems, notably dirty-paper coding. For this purpose, we start with a binary low-density generatormatrix (LDGM) code, and construct the quantization codebook by periodically repeating its set of binary codewords, or them mapped to m-ary ones with Gray mapping. The ...

The Exponentially Damped Sinusoids (EDS) model can efficiently represent real-world audio signals. In the context of low bit rate parametric audio coding, the EDS model could bring a significant improvement over classical sinusoidal models. The inclusion of an additional damping parameter calls for a specific quantization scheme. In this report, we describe a new jointscalar quantization scheme...

It has been asserted that temporal subband coding (TSB) is inferior to predictive coding for regionally motion compensated (e.g. block-based MC) temporally scalable compressed video [1]. There are two major disadvantages of TSB coding: temporal ltering distortions, and `open-loop' predictive coding of covered and uncovered regions. The `open-loop' structure of TSB coding, however, a ords two ma...