Method, apparatus and computer program product for providing improved data compression

• US 9,973,755 B2
• Filed: 08/23/2016
• Issued: 05/15/2018
• Est. Priority Date: 10/04/2007
• Status: Expired due to Fees

• Current Assignee: Conversant Wireless Licensing S.à.r.l. (f/k/a Core Wireless Licensing S.a.r.l.) (MOSAID Technologies Inc. (f/k/a Conversant Intellectual Property Management))
• Original Assignee: Conversant Wireless Licensing S.à.r.l. (f/k/a Core Wireless Licensing S.a.r.l.) (MOSAID Technologies Inc. (f/k/a Conversant Intellectual Property Management))
• Inventors: Nurminen, Jani K, Himanen, Sakari
• Primary Examiner(s): Hwa, Shyue Jiunn
• Application Number:
  US15/244,856
• Publication Number:
  US 20170085877A1
• Time in Patent Office: 630 Days
• CPC Class Codes: G06T 9/00 Image coding bandwidth or redundancy reduction for static pictures H04N1/41; coding or decoding of static colour picture signals H04N1/64; methods or arrangements for coding, decoding, compressing or decompressing digital video signals H04N19/00
• CPC Class Codes: G10L 19/032 Quantisation or dequantisation of spectral components
• CPC Class Codes: G10L 19/24 Variable rate codecs, e.g. for generating different qualities using a scalable representation such as hierarchical encoding or layered encoding
• CPC Class Codes: H04N 19/124 Quantisation
• CPC Class Codes: H04N 19/147 according to rate distortion criteria rate-distortion as a criterion for motion estimation H04N19/567
• CPC Class Codes: H04N 19/196 being specially adapted for the computation of encoding parameters, e.g. by averaging previously computed encoding parameters processing of motion vectors H04N19/513

Abstract

An apparatus for providing improved data compression may include an encoder comprising a quantizer for encoding input data and a side model. The quantizer may be trained with respect to high priority data among the input data and may be configured to partially encode the input data by encoding the high priority data. The side model may be trained jointly with the training of the quantizer and is configured to model low priority data among the input data.

Claims

1. A method to be performed on a decoder of a mobile device, the method comprising:

decoding, by a dequantizer of the decoder, compressed data to recover high priority data from a received signal, the high priority data being associated with spectral envelope data of spectral information of input data that was previously encoded as the received signal before the received signal was received, the input data corresponding to at least one of speech data, video data, image data, and audio data; and

recovering, by a side model of the decoder, low priority data from the received signal, the low priority data being associated with residual spectrum data comprising remaining parts of the spectral information other than the spectral envelope data of the input data, the side model being concurrently trained with the training of a quantizer used to encode the input signal, the quantizer trained with respect to the high priority data.

2. The method of claim 1, wherein the low priority data is not quantized and not encoded.

3. The method of claim 1, wherein the received signal comprises partially encoded input data, the input data being partially encoded by an encoder encoding high priority data among the input data using the quantizer.

4. The method of claim 1, wherein the received signal includes an indicator bit indicative of a sufficiency of the accuracy of the modeling of the low priority data and modeling error information for improving modeling accuracy when the indicator bit indicates insufficient modeling accuracy.

5. An apparatus comprising:

at least one processor; and

a decoder of a mobile device communicatively coupled to the at least one processor and comprising;

a dequantizer configured to decode compressed data to recover high priority data from a received signal, the high priority data being associated with spectral envelope data of spectral information of input data that was previously encoded as the received signal before the received signal was received, the input data corresponding to at least one of speech data, video data, image data, and audio data; and

a side model configured to recover low priority data from the received signal, the low priority data being associated with residual spectrum data comprising remaining parts of the spectral information other than the spectral envelope data of the input data, the side model being concurrently trained with the training of a quantizer used to encode the input signal, the quantizer trained with respect to the high priority data.

6. The apparatus of claim 5, wherein the low priority data is not quantized and not encoded.

7. The apparatus of claim 5, wherein the received signal comprises partially encoded input data, the input data being partially encoded by an encoder encoding high priority data among the input data using the quantizer.

8. The apparatus of claim 5, wherein the received signal includes an indicator bit indicative of a sufficiency of the accuracy of the modeling of the low priority data and modeling error information for improving modeling accuracy when the indicator bit indicates insufficient modeling accuracy.

9. A computer program product comprising at least one non-transitory computer-readable storage medium having computer-readable program code portions stored therein to be executed on a mobile device, the computer-readable program code portions comprising:

a first executable portion for decoding compressed data using a dequantizer module to recover high priority data from a received signal, the high priority data being associated with spectral envelope data of spectral information of input data that was previously encoded as the received signal before the received signal was received, the input data corresponding to at least one of speech data, video data, image data, and audio data; and

a second executable portion for recovering low priority data from the received signal using a side model module, the low priority data being associated with residual spectrum data comprising remaining parts of the spectral information other than the spectral envelope data of the input data, the side model module being concurrently trained with the training of a quantizer module used to encode the input signal, the quantizer module trained with respect to the high priority data.

10. The computer program product of claim 9, wherein the low priority data is not quantized and not encoded.

11. The computer program product of claim 9, wherein the received signal comprises partially encoded input data, the input data being partially encoded by an encoder encoding high priority data among the input data using the quantizer module.

12. The computer program product of claim 9, wherein the received signal includes an indicator bit indicative of a sufficiency of the accuracy of the modeling of the low priority data and modeling error information for improving modeling accuracy when the indicator bit indicates insufficient modeling accuracy.