Novel color processing architecture for digital cameras with CMOS image sensors

Weerasinghe, C.; Li, Wanqing; Kharitonenko, I.; Nilsson, Mats; Twelves, S.

doi:10.1109/tce.2005.1561829

Cited by 12 publications

(12 citation statements)

References 8 publications

(5 reference statements)

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“…As well known, CMOS image sensors suffer from high level noise and pixel cross-talk [2,14]. In order to achieve high quality images that are comparable to CCD image sensors, a new color processing chain, as shown in Figure 3, was proposed.…”

Section: Ptz Based Color Processingmentioning

confidence: 99%

“…The start addresses for accessing the CFA data are determined by the current pan and tilt values; whereas the address increment rate is determined by the current zoom value. Zoom values 1,2 and 4 are implemented in the camera [2,14].…”

Section: Color Interpolationmentioning

confidence: 99%

“…Under hardware constraints, a simple non-linear and hardware-friendly sharpening filter that proved its efficiency in [2,14] was implemented and employed in YUV color space. The filter has the following properties:…”

Section: Sharpness Enhancementmentioning

confidence: 99%

“…Figure 2 shows the architecture of proposed intelligent surveillance camera. The camera incorporates an automatic pan, tilt and zoom (PTZ) functionality implemented based upon [2,14] with the parameters decided upon captured activity within a specified region of interest (ROI). This provides more detailed visual information in zoomed modes while monitoring the full view at the same time.…”

Section: Introductionmentioning

confidence: 99%

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A Prototype of Autonomous Intelligent Surveillance Cameras

Kharitonenko

Lichman

et al. 2006

2006 IEEE International Conference on Video and Signal Based Surveillance

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This paper presents an architecture and an FPGAbased prototype of an autonomous intelligent video surveillance camera. The camera takes the advantage of high resolution of CMOS image sensors and enables instantly automatic pan, tilt and zoom adjustment based upon motion activity. It performs automated scene analysis and provides immediate response to suspicious events by optimizing camera capturing parameters. The video output of the camera can be optimized to any region of interest while the camera continues to monitor the entire scene. Field trials of the prototyped camera have verified the proposed architecture. Disciplines Physical Sciences and Mathematics

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Section: Ptz Based Color Processingmentioning

confidence: 99%

Section: Color Interpolationmentioning

confidence: 99%

Section: Sharpness Enhancementmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A Prototype of Autonomous Intelligent Surveillance Cameras

Kharitonenko

Lichman

et al. 2006

2006 IEEE International Conference on Video and Signal Based Surveillance

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“…[1][2][3] There are mainly two modules responsible for the color rendering accuracy in a digital camera: the former is the illuminant estimation and correction module, the latter is the color matrix transformation. These two modules together form what may be called the color correction pipeline.…”

Section: Introductionmentioning

confidence: 99%

Color correction pipeline optimization for digital cameras

Bianco¹,

Bruna²,

Naccari³

et al. 2013

J. Electron. Imaging

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Abstract. The processing pipeline of a digital camera converts the RAW image acquired by the sensor to a representation of the original scene that should be as faithful as possible. There are mainly two modules responsible for the color-rendering accuracy of a digital camera: the former is the illuminant estimation and correction module, and the latter is the color matrix transformation aimed to adapt the color response of the sensor to a standard color space. These two modules together form what may be called the color correction pipeline. We design and test new color correction pipelines that exploit different illuminant estimation and correction algorithms that are tuned and automatically selected on the basis of the image content. Since the illuminant estimation is an ill-posed problem, illuminant correction is not error-free. An adaptive color matrix transformation module is optimized, taking into account the behavior of the first module in order to alleviate the amplification of color errors. The proposed pipelines are tested on a publicly available dataset of RAW images. Experimental results show that exploiting the cross-talks between the modules of the pipeline can lead to a higher color-rendition accuracy. © The Authors. Published by SPIE under a Creative Commons Attribution 3.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.

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A method and results of color calibration for the Chang'e-3 terrain camera and panoramic camera

Ren¹,

Li²,

Liu³

et al. 2014

Res. Astron. Astrophys.

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The terrain camera (TCAM) and panoramic camera (PCAM) are two of the major scientific payloads installed on the lander and rover of the Chang'e 3 mission respectively. They both use a Bayer color filter array covering CMOS sensor to capture color images of the Moon's surface. RGB values of the original images are related to these two kinds of cameras. There is an obvious color difference compared with human visual perception. This paper follows standards published by the International Commission on Illumination to establish a color correction model, designs the ground calibration experiment and obtains the color correction coefficient. The image quality has been significantly improved and there is no obvious color difference in the corrected images. Ground experimental results show that: (1) Compared with uncorrected images, the average color difference of TCAM is 4.30, which has been reduced by 62.1%. (2) The average color differences of the left and right cameras in PCAM are 4.14 and 4.16, which have been reduced by 68.3% and 67.6% respectively.

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Novel color processing architecture for digital cameras with CMOS image sensors

Cited by 12 publications

References 8 publications

A Prototype of Autonomous Intelligent Surveillance Cameras

A Prototype of Autonomous Intelligent Surveillance Cameras

Color correction pipeline optimization for digital cameras

A method and results of color calibration for the Chang'e-3 terrain camera and panoramic camera

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