Compression system for integrated sensor devices

• US 7,751,634 B2
• Filed: 01/31/2007
• Issued: 07/06/2010
• Est. Priority Date: 04/10/2003
• Status: Active Grant

• Current Assignee: Micron Technology, Inc.
• Original Assignee: Micron Technology, Inc.
• Inventors: Venkataraman, Kartik
• Primary Examiner(s): TUCKER, WESLEY J
• Application Number:
  US11/700,090
• Publication Number:
  US 20070127831A1
• Time in Patent Office: 1,252 Days
• Field of Search: 382232-253
• US Class Current: 382/239
• 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 19/593 involving spatial prediction techniques
• CPC Class Codes: H04N 19/60 using transform coding
• CPC Class Codes: H04N 19/90 using coding techniques not provided for in groups H04N19/10-H04N19/85, e.g. fractals

Abstract

An imaging system incorporating adaptive compression which includes determining linear predictive differential residuals from an imager array pixel row. The differential residuals are classified into categories, each category having a range of differential residuals associated with it. The categories are analyzed to produce an ordered list having categories with most to least frequent residuals falling within a respective residual range associated with a respective category. The ordered list is then used to select a variable length encoding table with a matching ordered list. Variable length encoded category and range position offset data is output to a serializer unit, where the range position offset refers to a position in a range associated with a particular category.

Claims

1. An imager system comprising:

an imaging array comprising a plurality of pixels;

a processor circuit for outputting digital pixel signals representing incident light on the pixels of said array; and

a compression circuit for compressing said digital pixel signals by encoding said pixel signals such that sequential pixel signals in each row are each encoded as first and second transmission data determined based upon a plurality of first and second data, wherein;

said first data is based on differential pixel signals each determined from a corresponding one of a plurality of sets of sequential pixel signals;

said second data is determined based upon at least one categorization of said first data values by predetermined ordered ranges, said second data comprising an ordered sequence of category identifiers by frequency of occurrence within said ranges;

said first transmission data being assigned to said pixel signals from a selected codeword data set of a plurality of codeword data sets, said selected codeword data set being selected by matching said second data with one of said plurality of codeword data sets; and

said second transmission data is determined for each pixel signal based upon a category identifier assigned to said pixel and a position within said range associated with said category identifier.

2. An imager system of claim 1 wherein said plurality of first data comprises linear prediction differential residual data values for each channel of said plurality of pixels in a row.

3. An imager system of claim 1, wherein said plurality of second data comprises an ordered list of category identifiers for linear prediction differential residual data value ranges corresponding to said first data values.

4. An imager system of claim 1 wherein said second transmission data is a range position offset based upon ordered ranges associated with a category identifier, said offset relates to a position from a beginning of the ordered range associated with an associated category identifier.

5. An imager system of claim 1, wherein said codeword data sets comprise more than one variable length codeword.

6. An imager system of claim 1, wherein said codeword data sets comprise Huffman codes.

7. An imager system of claim 1 wherein said codeword data sets comprise Huffman coding tables, wherein each coding table stores codewords associated with a category identifier, said codewords are ordered from a most frequently occurring category identifier having a smallest codeword bit-size value to a least frequently occurring category identifier having a largest bit-size codeword value.

8. An imager system comprising:

an imaging array comprising a plurality of pixels;

a pixel signal processor circuit for outputting digital pixel signals representing incident light on the pixels of said array; and

a compression circuit for compressing said digital pixel signals by encoding said pixel signals such that sequential pixel signals in each row are each encoded with a codeword and a range position offset, said codewords determined based upon a plurality of first and second data, wherein;

said first data is based on differential pixel signals each determined from a corresponding one of a plurality of sets of sequential pixel signals;

said second data being determined based upon at least one categorization of said first data values by predetermined ordered ranges, said second data comprising an ordered sequence of category identifiers by frequency of occurrence associated within said ranges;

said codewords being assigned to said pixel signals from a selected codeword data set of a plurality of codeword data sets, said selected codeword data set being selected by matching said second data with one of said plurality of codeword data sets, each set comprises one or more category identifiers ordered with a different sequence than identifiers in other of said sets and an associated codeword; and

said range position offset for each pixel signal being determined based on a category identifier assigned to said pixel and the position within said range associated with said assigned category identifier.

9. An imager system of claim 8 wherein said plurality of first data comprises linear prediction differential residual data values for each channel of said plurality of pixels in a row.

10. An imager system of claim 8, wherein said plurality of second data comprises an ordered list of category identifiers for linear prediction differential residual data value ranges corresponding to said first data values.

11. An imager system of claim 8, wherein said range position offset is based upon ordered ranges associated with a category identifier, said offset being related to position from the beginning of the ordered range associated with an associated category identifier.

12. An imager system of claim 8, further comprising either a CMOS or CCD sensor.

13. An imager system of claim 8, wherein said plurality of second data is based upon probability density function data for said plurality of first data.

14. A method of performing image data compression comprising:

reading a plurality of pixel signals from a selected pixel row in an image sensor;

determining a plurality of first data based on differential pixel signals each determined from a corresponding one of a plurality of sets of sequential pixel signals;

determining a plurality of second data based upon at least one categorization of said first data, said second data comprising an ordered sequence of category identifiers by frequency of occurrence within an ordered range;

determining first transmission data for each pixel signal from a selected codeword data set of a plurality of codeword data sets, said selected codeword data set being selected by matching said second data with one of said plurality of codeword data sets;

determining a second transmission data for each pixel signal based upon a said category identifier assigned to said pixel and position within a range associated with said category identifier; and

outputting encoded pixel signals such that each pixel signal in each row is encoded with said first and second transmission data.

15. A method as in claim 14, wherein said plurality of first data comprises linear prediction differential residual data values for each channel of said plurality of pixels in a row.

16. A method as in claim 14, wherein said plurality of second data comprises an ordered list of category identifiers for linear prediction differential residual data value ranges corresponding to said first data.

17. A method as in claim 14, wherein said second transmission data is a range position offset based upon ordered ranges associated with a category identifier.

18. A method as in claim 14, wherein said codeword data sets comprise more than one variable length codeword.

19. A method as in claim 14, wherein said codeword data sets comprise tables comprising Huffman codes.

20. A method as in claim 14, wherein said plurality of second data is based upon probability density function data for said plurality of first data.