Examples described herein relate to decoding and encoding signals. Certain examples described herein encapsulate custom data that is not signal data within a stream of encoded signal data. The custom data may comprise a wide variety of metadata that annotates the signal data, or provides additional information relating to the signal data. Certain examples described herein encapsulate custom data within a set of transformed coefficient values that represent data derived from a transform operation that forms part of the signal encoding. The encapsulation is may be performed by applying a bit shift operation to coefficient bits representing the set of transformed coefficient values.

Examples described herein relate to decoding and encoding signals. Certain examples described herein encapsulate custom data that is not signal data within a stream of encoded signal data. The custom data may comprise a wide variety of metadata that annotates the signal data, or provides additional information relating to the signal data. Certain examples described herein encapsulate custom data within a set of transformed coefficient values that represent data derived from a transform operation that forms part of the signal encoding. The encapsulation is may be performed by applying a bit shift operation to coefficient bits representing the set of transformed coefficient values.

A lossy method of compressing data, such as image data, which uses wrap-around wavelet compression is described. Each data value is divided into two parts and the first parts, which comprise the most significant bits from the data values, are compressed using wrap-around wavelet compression. Depending upon the target compression ratio and the compression ratio achieved by compressing just the first parts, none, one or more bits from the second parts, or from a data value derived from the second parts, may be appended to the compressed first parts. The method described may be lossy or may be lossless. A corresponding decompression method is also described.

A lossy method of compressing data, such as image data, which uses wrap-around wavelet compression is described. Each data value is divided into two parts and the first parts, which comprise the most significant bits from the data values, are compressed using wrap-around wavelet compression. Depending upon the target compression ratio and the compression ratio achieved by compressing just the first parts, none, one or more bits from the second parts, or from a data value derived from the second parts, may be appended to the compressed first parts. The method described may be lossy or may be lossless. A corresponding decompression method is also described.

Techniques and tools for encoding enhancement layer video with quantization that varies spatially and/or between color channels are presented, along with corresponding decoding techniques and tools. For example, an encoding tool determines whether quantization varies spatially over a picture, and the tool also determines whether quantization varies between color channels in the picture. The tool signals quantization parameters for macroblocks in the picture in an encoded bit stream. In some implementations, to signal the quantization parameters, the tool predicts the quantization parameters, and the quantization parameters are signaled with reference to the predicted quantization parameters. A decoding tool receives the encoded bit stream, predicts the quantization parameters, and uses the signaled information to determine the quantization parameters for the macroblocks of the enhancement layer video. The decoding tool performs inverse quantization that can vary spatially and/or between color channels.

Techniques and tools for encoding enhancement layer video with quantization that varies spatially and/or between color channels are presented, along with corresponding decoding techniques and tools. For example, an encoding tool determines whether quantization varies spatially over a picture, and the tool also determines whether quantization varies between color channels in the picture. The tool signals quantization parameters for macroblocks in the picture in an encoded bit stream. In some implementations, to signal the quantization parameters, the tool predicts the quantization parameters, and the quantization parameters are signaled with reference to the predicted quantization parameters. A decoding tool receives the encoded bit stream, predicts the quantization parameters, and uses the signaled information to determine the quantization parameters for the macroblocks of the enhancement layer video. The decoding tool performs inverse quantization that can vary spatially and/or between color channels.

Provided is a scalable video-decoding method based on multiple layers. The scalable video-decoding method according to the present invention comprises: a step of predicting first filter information of a video to be filtered using the information contained in an object layer and/or information contained in another layer, and generating second filter information in accordance with the prediction; and a step of filtering the video to be filtered using the second filter information. According to the present invention, the amount of information being transmitted is reduced, and video compression performance is improved.

Provided is a scalable video-decoding method based on multiple layers. The scalable video-decoding method according to the present invention comprises: a step of predicting first filter information of a video to be filtered using the information contained in an object layer and/or information contained in another layer, and generating second filter information in accordance with the prediction; and a step of filtering the video to be filtered using the second filter information. According to the present invention, the amount of information being transmitted is reduced, and video compression performance is improved.

Techniques and tools for encoding enhancement layer video with quantization that varies spatially and/or between color channels are presented, along with corresponding decoding techniques and tools. For example, an encoding tool determines whether quantization varies spatially over a picture, and the tool also determines whether quantization varies between color channels in the picture. The tool signals quantization parameters for macroblocks in the picture in an encoded bit stream. In some implementations, to signal the quantization parameters, the tool predicts the quantization parameters, and the quantization parameters are signaled with reference to the predicted quantization parameters. A decoding tool receives the encoded bit stream, predicts the quantization parameters, and uses the signaled information to determine the quantization parameters for the macroblocks of the enhancement layer video. The decoding tool performs inverse quantization that can vary spatially and/or between color channels.

Techniques and tools for encoding enhancement layer video with quantization that varies spatially and/or between color channels are presented, along with corresponding decoding techniques and tools. For example, an encoding tool determines whether quantization varies spatially over a picture, and the tool also determines whether quantization varies between color channels in the picture. The tool signals quantization parameters for macroblocks in the picture in an encoded bit stream. In some implementations, to signal the quantization parameters, the tool predicts the quantization parameters, and the quantization parameters are signaled with reference to the predicted quantization parameters. A decoding tool receives the encoded bit stream, predicts the quantization parameters, and uses the signaled information to determine the quantization parameters for the macroblocks of the enhancement layer video. The decoding tool performs inverse quantization that can vary spatially and/or between color channels.