Methods, systems, and computer programs for improved quality video compression. Image quality from MPEG-style video coding may be improved by preserving a higher number of bits during intermediate encoding and decoding processing steps. Problems of inverse discrete cosine transform (IDCT) mismatch can be eliminated by exactly matching the IDCT function numerical algorithm of the decoder to the IDCT function numerical algorithm used for the decoding portion of the encoder. Also included is an application of high precision compression to wide dynamic range images by extending the range of the “quantization parameter” or “QP”. The extension of QP may be accomplished either by increasing the range of QP directly, or indirectly through a non-linear transformation. Also included is an application of extended intermediate processing precision and an extended QP range to reduced contrast regions of an image to extend the precision with which the low-contrast portions are compression coded.

High precision encoding and decoding of video images

A compression system and process include adaptive quantization for selection of one quantizer, for each video frame or frame portion, from a group of quantizers, where each quantizer is a set of predefined quantizer values, and coding of the quantized values using a common entropy coding table for all quantizers, or a separate entropy coding table for each quantizer. The entropy coding tables are obtained during a training procedure. The selection of the quantizer is based on a formula which takes into account the distortion and bit rate characteristics of each quantizer. A similar formula, based on the distortion and bit rate characteristics, is used to select the particular quantizer value within the chosen quantizer for each video signal value being coded.

Adaptive entropy coding in adaptive quantization framework for video signal coding systems and processes

Entropy coding and decoding techniques are described, which may be implemented separately or in combination. For example, a video encoder uses two-layer run level coding to reduce bitrate for frequency transform coefficients in a quick and efficient manner, and a video decoder uses corresponding two-layer run level decoding. This two-layer coding/decoding can be generalized to more than two layers of run level coding/decoding. The video encoder and decoder exploit common patterns in run level information to reduce code table size and create opportunities for early termination of decoding. Using zoned Huffman code tables helps limit overall table size while still providing a level of adaptivity in encoding and decoding. Using embedded Huffman code tables allows the encoder and decoder to reuse codes for 8×8, 8×4, 4×8, and 4×4 blocks.

Multi-layer run level encoding and decoding

Method and system for wireless communication adapted for compressing data prior to its transmission. Data compression may be limited or skipped when it is determined that tlie data compression may cause an unacceptable amount or data to be lost. Abnormal situation detection as part of data compression is included. Methods associated with such systems are also encompassed.

Data compression and abnormal situation detection in a wireless sensor network

An audio encoder performs adaptive entropy encoding of audio data. For example, an audio encoder switches between variable dimension vector Huffman coding of direct levels of quantized audio data and run-level coding of run lengths and levels of quantized audio data. The encoder can use, for example, context-based arithmetic coding for coding run lengths and levels. The encoder can determine when to switch between coding modes by counting consecutive coefficients having a predominant value (e.g., zero). An audio decoder performs corresponding adaptive entropy decoding.

Entropy coding by adapting coding between level and run-length/level modes.

A compression system and process employs a group of quantizers (or set of predefined quantized values) and involves the selection of the quantizers for each video frame or frame portion. For each frame portion, a selection of the most appropriate quantizer is made. The selection of which quantizer from the selection group is most appropriate for coding of a video frame or frame portion is based on a formula which takes account both the distortion (accuracy) and bit rate characteristics of each quantizer. The quantizer that exhibits the best combined distortion and bit rate characteristics is selected for coding the frame or frame portion. A similar formula, based on both distortion and bit rate characteristics, is used to select the particular quantization value within the quantizer set for each video signal value being coded.

Parthasarathy Sriram

Papers

Video signal coding systems and processes using adaptive quantization