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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.


Experimental results using the parking garage image: (a) The reference image with ISO 3200 (EV = +1); (b) one-step lower image using ISO 800 (EV = −1); (c) enhanced image of (b) using ordinary four-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 algorithm.
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sensors-15-14917-f008: Experimental results using the parking garage image: (a) The reference image with ISO 3200 (EV = +1); (b) one-step lower image using ISO 800 (EV = −1); (c) enhanced image of (b) using ordinary four-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 algorithm.

Mentions: Figure 8 shows the experimental results of enhancing a typical low-light image acquired under low illumination of under 8 lux. Two input test images are acquired using different ISO values of 3200 and 800, and fixed aperture size F5.6 and shutter speed 1/15 s.


Low-Light Image Enhancement Using Adaptive Digital Pixel Binning.

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

Experimental results using the parking garage image: (a) The reference image with ISO 3200 (EV = +1); (b) one-step lower image using ISO 800 (EV = −1); (c) enhanced image of (b) using ordinary four-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 algorithm.
© Copyright Policy
Related In: Results  -  Collection

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

sensors-15-14917-f008: Experimental results using the parking garage image: (a) The reference image with ISO 3200 (EV = +1); (b) one-step lower image using ISO 800 (EV = −1); (c) enhanced image of (b) using ordinary four-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 algorithm.
Mentions: Figure 8 shows the experimental results of enhancing a typical low-light image acquired under low illumination of under 8 lux. Two input test images are acquired using different ISO values of 3200 and 800, and fixed aperture size F5.6 and shutter speed 1/15 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.