Codebook improvements for a CMOS imager with focal-plane vector quantization

In previous works a 32 × 32 pixel CMOS image sensor featuring focal-plane image compression based on differential pulse-code modulation and vector quantization was presented. Images compressed with this imager were reconstructed at peak signal-to-noise ratios around 18 dB, for bit rates below 0.94 bit per pixel. In this work, we focus on the improvement of the vector quantization stage of the previously proposed imager. We use experimentally captured photographs to update the code-book that is used at the decoder side. With the new codebooks, we are able to reconstruct texture feature vectors with a mean squared error (MSE) that is consistently smaller than the MSE obtained with the originally designed codebook.

[1]  Tracy L. Faber Next generation artificial vision systems: reverse engineering the human visual system , 2009 .

[2]  Allen Gersho,et al.  Vector quantization and signal compression , 1991, The Kluwer international series in engineering and computer science.

[3]  Thomas M. Cover,et al.  Elements of Information Theory , 2005 .

[4]  Ángel Rodríguez-Vázquez,et al.  ACE16k: the third generation of mixed-signal SIMD-CNN ACE chips toward VSoCs , 2004, IEEE Transactions on Circuits and Systems I: Regular Papers.

[5]  Orly Yadid-Pecht,et al.  Adaptive multiple resolution CMOS active pixel sensor , 2004 .

[6]  Jun Ohta,et al.  Smart CMOS Image Sensors and Applications , 2007 .

[7]  Philip A. Chou,et al.  Entropy-constrained vector quantization , 1989, IEEE Trans. Acoust. Speech Signal Process..

[8]  José Gabriel Rodríguez Carneiro Gomes,et al.  Computation of the complexity of vector quantizers by affine modeling , 2011, Signal Process..

[9]  David Salomon,et al.  Data compression - The Complete Reference, 4th Edition , 2004 .

[10]  Amine Bermak,et al.  A CMOS Image Sensor With On-Chip Image Compression Based on Predictive Boundary Adaptation and Memoryless QTD Algorithm , 2011, IEEE Transactions on Very Large Scale Integration (VLSI) Systems.

[11]  Junichi Nakamura,et al.  Image Sensors and Signal Processing for Digital Still Cameras , 2005 .

[12]  Michael W. Hoffman,et al.  A CMOS Imager With Focal Plane Compression Using Predictive Coding , 2007, IEEE Journal of Solid-State Circuits.

[13]  R. Genov,et al.  Focal-Plane Algorithmically-Multiplying CMOS Computational Image Sensor , 2009, IEEE Journal of Solid-State Circuits.

[14]  Antonio Petraglia,et al.  CMOS Imager With Focal-Plane Analog Image Compression Combining DPCM and VQ , 2013, IEEE Transactions on Circuits and Systems I: Regular Papers.