A new digital signal processor for progressive scan CCD

Zen, Heishun; Koizumi, Takashi; Yamamoto, Hideo; Kimura, I.

doi:10.1109/30.681940

Cited by 26 publications

(2 citation statements)

References 3 publications

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“…Thus, image processing will likely take place in an embedded platform. Bayer conversion in hardware is not a new innovation, with image enhancement available for both CMOS [19] and CCD [20] sensors. Typically, the raw Bayer data is demosaiced, before gamma correction, color correction, white balancing, and contrast enhancement is applied.…”

Section: Designing a Low-cost Spectrometermentioning

confidence: 99%

INSPEC<sup>2</sup>T: Inexpensive Spectrometer Color Camera Technology

Scheirer

Kirkbride

Boult

2008

2008 IEEE Workshop on Applications of Computer Vision

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Modern spectrometer equipment tends to be expensive, thus increasing the cost of emerging systems that take advantage of spectral properties as part of their operation. This paper introduces a novel technique that exploits the spectral response characteristics of a traditional sensor (i.e. CMOS or CCD) to utilize it as a low-cost spectrometer. Using the raw Bayer pattern data from a sensor, we estimate the brightness and wavelength of the measured light at a particular point. We use this information to support wide dynamic range, high noise tolerance, and, if sampling takes place on a slope, sub-pixel resolution. Experimental results are provided for both simulation and real data. Further, we investigate the potential of this low-cost technology for spoof detection in biometric systems. Lastly, an actual hardware systhsis is conducted to show the ease with which this algorthim can be implemented onto an FPGA.

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Section: Designing a Low-cost Spectrometermentioning

confidence: 99%

INSPEC<sup>2</sup>T: Inexpensive Spectrometer Color Camera Technology

Scheirer

Kirkbride

Boult

2008

2008 IEEE Workshop on Applications of Computer Vision

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“…It is identified that most of the existing techniques (Menon et al, 2007;Chung and Chan, 2006;Su, 2006;Gunturk et al, 2002;Li, 2005;Zen et al, 1998) have not considered the level of smoothness of smoother region during interpolation. Poor quality on smoother region in demosaiced image has resulted due to this problem.…”

Section: Introductionmentioning

confidence: 99%

Edge Sensing Demosaicing Using Adaptive Weighted Interpolation

Newlin¹,

Monie²

2013

American Journal of Applied Sciences

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Demosaicing is a process of obtaining a full color image by interpolating the missing colors of an image captured from a digital still and video cameras that use a single-sensor array.The edges are not handled properly in the existing demosaicking methods. This study provides an effective demosaicing algorithm applying an adaptive weighted-edge interpolation to handle green pixels. Due to the introduction of adaptive threshold based on the high frequency information for the classification of edges and textures, the interpolation of edges is performed excellently. Adaptive weights depending on spatial and spectral correlation are assigned for interpolation on both edges and smooth region. A refinement scheme based on enhanced effective color interpolation is used to improve the red and blue interpolation to obtain better quality image. As compared with the latest demosaicing algorithms, the proposed algorithm produces the best average demosaicing performance both objectively and subjectively. This approach handles the edges in a proper way and reconstructs the color image with best peak signal to noise ratio

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Super‐resolution approach to overcome physical limitations of imaging sensors: An overview

Choi

Kang

2004

Int J Imaging Syst Tech

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Although the performance of CCD and CMOS imaging sensors has improved since their invention, they still have several physical limitations, such as various sources of noise, limited dynamic range, and limited spatial resolution. Besides these physical limitations, they have malfunctioning problems, such as smearing and blooming, which degrade the quality of captured images. These limitations and malfunctioning problems can be overcome, based on device physics and circuit technology. However, a signal-processingbased approach is a good alternative solution to these problems, because it may cost less and existing imaging systems can be still utilized. In a broad sense, this signal-processing-based approach can be called a super-resolution approach. The goal of this article is to introduce a super-resolution approach that overcomes the limitations of imaging sensors. To this purpose, we describe the existing limitations of imaging sensors first, and then describe the corresponding super-resolution approach.

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A new digital signal processor for progressive scan CCD

Cited by 26 publications

References 3 publications

INSPEC<sup>2</sup>T: Inexpensive Spectrometer Color Camera Technology

INSPEC<sup>2</sup>T: Inexpensive Spectrometer Color Camera Technology

Edge Sensing Demosaicing Using Adaptive Weighted Interpolation

Super‐resolution approach to overcome physical limitations of imaging sensors: An overview

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