Method and apparatus for compression using reversible wavelet transforms and an embedded codestream

• US 7,068,849 B2
• Filed: 08/22/2002
• Issued: 06/27/2006
• Est. Priority Date: 09/21/1994
• Status: Expired due to Fees

• Current Assignee: Ricoh Company Limited, Ricoh Corporation (Ricoh Company Limited)
• Original Assignee: Ricoh Company Limited, Ricoh Corporation (Ricoh Company Limited)
• Inventors: Gormish, Michael J., Schwartz, Edward L., Boliek, Martin, Zandi, Ahmad
• Primary Examiner(s): Tran, Phuoc
• Application Number:
  US10/226,853
• Publication Number:
  US 20030123743A1
• Time in Patent Office: 1,405 Days
• Field of Search: 382/240, 382/248, 375/240.19
• US Class Current: 382/240
• CPC Class Codes: G06F 17/148 Wavelet transforms
• CPC Class Codes: H03M 7/30 Compression speech analysis-synthesis for redundancy reduction G10L19/00; for image communication H04N; Expansion; Suppression of unnecessary data, e.g. redundancy reduction
• CPC Class Codes: H04N 19/102 characterised by the element, parameter or selection affected or controlled by the adaptive coding
• CPC Class Codes: H04N 19/115 Selection of the code volume for a coding unit prior to coding
• CPC Class Codes: H04N 19/12 Selection from among a plurality of transforms or standards, e.g. selection between discrete cosine transform [DCT] and sub-band transform or selection between H.263 and H.264
• CPC Class Codes: H04N 19/122 Selection of transform size, e.g. 8x8 or 2x4x8 DCT; Selection of sub-band transforms of varying structure or type
• CPC Class Codes: H04N 19/129 Scanning of coding units, e.g. zig-zag scan of transform coefficients or flexible macroblock ordering [FMO]
• CPC Class Codes: H04N 19/13 Adaptive entropy coding, e.g. adaptive variable length coding [AVLC] or context adaptive binary arithmetic coding [CABAC]
• CPC Class Codes: H04N 19/146 Data rate or code amount at the encoder output
• CPC Class Codes: H04N 19/15 by monitoring actual compressed data size at the memory before deciding storage at the transmission buffer
• CPC Class Codes: H04N 19/156 Availability of hardware or computational resources, e.g. encoding based on power-saving criteria
• CPC Class Codes: H04N 19/162 User input
• CPC Class Codes: H04N 19/167 Position within a video image, e.g. region of interest [ROI]
• CPC Class Codes: H04N 19/186 the unit being a colour or a chrominance component
• CPC Class Codes: H04N 19/1883 the unit relating to sub-band structure, e.g. hierarchical level, directional tree, e.g. low-high [LH], high-low [HL], high-high [HH]
• CPC Class Codes: H04N 19/34 Scalability techniques involving progressive bit-plane based encoding of the enhancement layer, e.g. fine granular scalability [FGS]
• CPC Class Codes: H04N 19/36 Scalability techniques involving formatting the layers as a function of picture distortion after decoding, e.g. signal-to-noise [SNR] scalability
• CPC Class Codes: H04N 19/42 characterised by implementation details or hardware specially adapted for video compression or decompression, e.g. dedicated software implementation H04N19/635 takes precedence
• CPC Class Codes: H04N 19/46 Embedding additional information in the video signal during the compression process H04N19/517, H04N19/68, H04N19/70 take precedence
• CPC Class Codes: H04N 19/593 involving spatial prediction techniques
• CPC Class Codes: H04N 19/60 : using transform coding
• CPC Class Codes: H04N 19/61 : in combination with predictive coding
• CPC Class Codes: H04N 19/63 : using sub-band based transform, e.g. wavelets
• CPC Class Codes: H04N 19/635 : characterised by filter definition or implementation details
• CPC Class Codes: H04N 19/647 : using significance based coding, e.g. Embedded Zerotrees of Wavelets [EZW] or Set Partitioning in Hierarchical Trees [SPIHT]
• CPC Class Codes: H04N 19/98 : Adaptive-dynamic-range coding [ADRC]
• CPC Class Codes: H04N 21/6377 : directed to server one-way streaming services wherein the source is controlled by the destination H04L65/613
• CPC Class Codes: H04N 21/658 : Transmission by the client directed to the server

Abstract

A compression and decompression system in which a reversible wavelet filter are used to generates coefficients from input data, such as image data. The reversible wavelet filter is an efficient transform implemented with integer arithmetic that has exact reconstruction. The present invention uses the reversible wavelet filter in a lossless system (or lossy system) in which an embedded codestream is generated from the coefficients produced by the filter. An entropy coder performs entropy coding on the embedded codestream to produce the compressed data stream.

Claims

1. An apparatus comprising:

a wavelet transform to generate wavelet coefficients;

a model to model the wavelet coefficients from the wavelet transform as part of a process to generate coded data;

a channel manager to control rate at which the coded data is transmitted to a limited bandwidth channel, the coded data being categorized based on significance;

wherein the channel manager permits transmission of all coded data onto the limited bandwidth channel if bandwidth is available and discards less significant data to enable transmission of more significant data if bandwidth is not available; and

wherein the channel manager determines significance for portions of the coded data using a threshold.

2. The apparatus defined in claim 1 wherein the wavelet transform comprises a reversible wavelet transform.

3. The apparatus defined in claim 1 wherein the channel manager divides the coded data based on significance.

4. The apparatus defined in claim 1 wherein the channel manager includes a memory to store coded data and overwrites less important data when the memory is full.

5. The apparatus defined in claim 1 wherein the channel manager prevents transmission of coded data categorized as less significance, where significance is determined based on a threshold.

6. The apparatus defined in claim 1 wherein the limited bandwidth channel indicates its bandwidth to the channel manager.

7. The apparatus defined in claim 1 wherein tiles in the coded data are categorized based on the significance.

8. An apparatus comprising:

a wavelet transform to generate wavelet coefficients;

a model to model the wavelet coefficients from the wavelet transform as part of a process to generate coded data; and

a channel manager to control rate at which the coded data is transmitted to a limited bandwidth channel, the coded data being categorized based on significance, wherein the channel manager dynamically determines the bandwidth of the limited bandwidth channel based on the amount of time expended in sending a predetermined packet of data through the channel.

9. A method comprising:

generating wavelet coefficients using a wavelet transform;

modeling the wavelet coefficients from the wavelet transform as part of a process to generate coded data;

determining significance for portions of the coded data using a threshold; and

controlling rate at which the coded data is transmitted to a limited bandwidth channel, the coded data being categorized based on significance, wherein controlling rate at which the coded data is transmitted to a limited bandwidth channel comprises permitting transmission of all coded data onto the limited bandwidth channel if bandwidth is available and discards less significant data to enable transmission of more significant data if bandwidth is not available.

10. The method defined in claim 9 wherein the wavelet transform comprises a reversible wavelet transform.

11. The method defined in claim 9 wherein controlling rate at which the coded data is transmitted to a limited bandwidth channel comprises dividing the coded data based on significance.

12. The method defined in claim 9 further comprising:

storing coded data in a memory; and

overwriting less important data in the memory when the memory is full.

13. The method defined in claim 9 wherein controlling rate at which the coded data is transmitted to a limited bandwidth channel comprises preventing transmission of coded data categorized as less significance, where significance is determined based on a threshold.

14. The method defined in claim 9 further comprises the limited bandwidth channel indicating its bandwidth to a channel manager.

15. The method defined in claim 9 wherein tiles in the coded data are categorized based on the significance.

16. A method comprising:

generating wavelet coefficients using a wavelet transform;

modeling the wavelet coefficients from the wavelet transform as part of a process to generate coded data;

dynamically determining the bandwidth of the limited bandwidth channel based on the amount of time expended in sending a predetermined packet of data through the channel, and

controlling rate at which the coded data is transmitted to a limited bandwidth channel, the coded data being categorized based on significance.

17. An article of manufacturing having one or more machine-readable media storing instructions which, when executed by a machine, cause the machine to:

generate wavelet coefficients using a wavelet transform;

model the wavelet coefficients from the wavelet transform as part of a process to generate coded data;

determine significance for portions of the coded data using a threshold; and

control rate at which the coded data is transmitted to a limited bandwidth channel, the coded data being categorized based on significance, wherein controlling rate at which the coded data is transmitted to a limited bandwidth channel comprises permitting transmission of all coded data onto the limited bandwidth channel if bandwidth is available and discards less significant data to enable transmission of more significant data if bandwidth is not available.

18. An article of manufacturing having one or more machine-readable media storing instructions which, when executed by a machine, cause the machine to:

generate wavelet coefficients using a wavelet transform;

model the wavelet coefficients from the wavelet transform as part of a process to generate coded data;

control rate at which the coded data is transmitted to a limited bandwidth channel, the coded data being categorized based on significance; and

dynamic determining the bandwidth of the limited bandwidth channel based on the amount of time expended in sending a predetermined packet of data through the channel.