Compressive acquisition CMOS image sensor

From the algorithm to hardware implementation

Milin Zhang, Amine Bermak

Research output: Contribution to journalArticle

34 Citations (Scopus)

Abstract

In this paper, a new design paradigm referred to as compressive acquisition CMOS image sensors is introduced. The idea consists of compressing the data within each pixel prior to storage, and hence, reducing the size of the memory required for digital pixel sensor. The proposed compression algorithm uses a block-based differential coding scheme in which differential values are captured and quantized online. A time-domain encoding scheme is used in our CMOS image sensor in which the brightest pixel within each block fires first and is selected as the reference pixel. The differential values between subsequent pixels and the reference within each block are calculated and quantized, using a reduced number of bits as their dynamic range is compressed. The proposed scheme enables reduced error accumulation as full precision is used at the start of each block, while also enabling reduced memory requirement, and hence, enabling significant silicon area saving. A mathematical model is derived to analyze the performance of the algorithm. Experimental results on a field-programmable gate-array (FPGA) platform illustrate that the proposed algorithm enables more than 50% memory saving at a peak signal-to-noise ratio level of 30 dB with 1.5 bit per pixel.

Original languageEnglish
Article number4814495
Pages (from-to)490-500
Number of pages11
JournalIEEE Transactions on Very Large Scale Integration (VLSI) Systems
Volume18
Issue number3
DOIs
Publication statusPublished - Mar 2010
Externally publishedYes

Fingerprint

Image sensors
Pixels
Hardware
Data storage equipment
Field programmable gate arrays (FPGA)
Signal to noise ratio
Fires
Mathematical models
Silicon
Sensors

Keywords

  • Compressive acquisition
  • Differential pulse code modulation (DPCM)
  • Digital pixel sensors (DPSs)
  • Online block-based compression algorithm

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Hardware and Architecture
  • Software

Cite this

Compressive acquisition CMOS image sensor : From the algorithm to hardware implementation. / Zhang, Milin; Bermak, Amine.

In: IEEE Transactions on Very Large Scale Integration (VLSI) Systems, Vol. 18, No. 3, 4814495, 03.2010, p. 490-500.

Research output: Contribution to journalArticle

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