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Low-Light Image Enhancement Using Adaptive Digital Pixel Binning.

Yoo Y, Im J, Paik J - Sensors (Basel) (2015)

Bottom Line: This paper presents an image enhancement algorithm for low-light scenes in an environment with insufficient illumination.Simple amplification of intensity exhibits various undesired artifacts: noise amplification, intensity saturation, and loss of resolution.Since the proposed algorithm does not use an iterative computation, it can be easily embedded in an existing digital camera ISP pipeline containing a high-resolution image sensor.

View Article: PubMed Central - PubMed

Affiliation: Image Processing and Intelligent Systems Laboratory Graduate School of Advanced Imaging Science, Multimedia, and Film Chung-Ang University, Seoul 156-756, Korea. whitener@cau.ac.kr.

ABSTRACT
This paper presents an image enhancement algorithm for low-light scenes in an environment with insufficient illumination. Simple amplification of intensity exhibits various undesired artifacts: noise amplification, intensity saturation, and loss of resolution. In order to enhance low-light images without undesired artifacts, a novel digital binning algorithm is proposed that considers brightness, context, noise level, and anti-saturation of a local region in the image. The proposed algorithm does not require any modification of the image sensor or additional frame-memory; it needs only two line-memories in the image signal processor (ISP). Since the proposed algorithm does not use an iterative computation, it can be easily embedded in an existing digital camera ISP pipeline containing a high-resolution image sensor.

No MeSH data available.


Related in: MedlinePlus

Enhancement results using the ISO 12233 resolution chart image: (a) The reference image with ISO 3200 (EV = 0); (b) one-step lower exposure image using ISO 1600 (EV = −1); (c) enhanced image of (b) using the ordinary two-pixel digital pixel binning; (d) enhanced image of (b) using Kim’s algorithm; (e) enhanced image of (b) using Jiang’s algorithm; and (f) enhanced image of (b) using the adaptive four-pixel digital pixel binning.
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sensors-15-14917-f006: Enhancement results using the ISO 12233 resolution chart image: (a) The reference image with ISO 3200 (EV = 0); (b) one-step lower exposure image using ISO 1600 (EV = −1); (c) enhanced image of (b) using the ordinary two-pixel digital pixel binning; (d) enhanced image of (b) using Kim’s algorithm; (e) enhanced image of (b) using Jiang’s algorithm; and (f) enhanced image of (b) using the adaptive four-pixel digital pixel binning.

Mentions: Figure 6 shows the experimental results of enhancing the ISO 12233 resolution chart image under 15 lux illumination. Three test images are acquired using different ISO values including 3200 and 1600, fixed aperture size F11, and shutter speed 1/16 s.


Low-Light Image Enhancement Using Adaptive Digital Pixel Binning.

Yoo Y, Im J, Paik J - Sensors (Basel) (2015)

Enhancement results using the ISO 12233 resolution chart image: (a) The reference image with ISO 3200 (EV = 0); (b) one-step lower exposure image using ISO 1600 (EV = −1); (c) enhanced image of (b) using the ordinary two-pixel digital pixel binning; (d) enhanced image of (b) using Kim’s algorithm; (e) enhanced image of (b) using Jiang’s algorithm; and (f) enhanced image of (b) using the adaptive four-pixel digital pixel binning.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4541814&req=5

sensors-15-14917-f006: Enhancement results using the ISO 12233 resolution chart image: (a) The reference image with ISO 3200 (EV = 0); (b) one-step lower exposure image using ISO 1600 (EV = −1); (c) enhanced image of (b) using the ordinary two-pixel digital pixel binning; (d) enhanced image of (b) using Kim’s algorithm; (e) enhanced image of (b) using Jiang’s algorithm; and (f) enhanced image of (b) using the adaptive four-pixel digital pixel binning.
Mentions: Figure 6 shows the experimental results of enhancing the ISO 12233 resolution chart image under 15 lux illumination. Three test images are acquired using different ISO values including 3200 and 1600, fixed aperture size F11, and shutter speed 1/16 s.

Bottom Line: This paper presents an image enhancement algorithm for low-light scenes in an environment with insufficient illumination.Simple amplification of intensity exhibits various undesired artifacts: noise amplification, intensity saturation, and loss of resolution.Since the proposed algorithm does not use an iterative computation, it can be easily embedded in an existing digital camera ISP pipeline containing a high-resolution image sensor.

View Article: PubMed Central - PubMed

Affiliation: Image Processing and Intelligent Systems Laboratory Graduate School of Advanced Imaging Science, Multimedia, and Film Chung-Ang University, Seoul 156-756, Korea. whitener@cau.ac.kr.

ABSTRACT
This paper presents an image enhancement algorithm for low-light scenes in an environment with insufficient illumination. Simple amplification of intensity exhibits various undesired artifacts: noise amplification, intensity saturation, and loss of resolution. In order to enhance low-light images without undesired artifacts, a novel digital binning algorithm is proposed that considers brightness, context, noise level, and anti-saturation of a local region in the image. The proposed algorithm does not require any modification of the image sensor or additional frame-memory; it needs only two line-memories in the image signal processor (ISP). Since the proposed algorithm does not use an iterative computation, it can be easily embedded in an existing digital camera ISP pipeline containing a high-resolution image sensor.

No MeSH data available.


Related in: MedlinePlus