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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.


The magnified version of the red box shown in Figure 10a: (a) The reference image with 18 dB gain; (b) underexposed image with 12 dB gain; (c) enhanced image of (b) using 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 algorithm.
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sensors-15-14917-f011: The magnified version of the red box shown in Figure 10a: (a) The reference image with 18 dB gain; (b) underexposed image with 12 dB gain; (c) enhanced image of (b) using 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 algorithm.

Mentions: Figure 10a,b respectively show 18 dB and 12 dB AFE gain images. Figure 10c shows the brightness-enhanced image of Figure 10b using the ordinary digital pixel binning with the horizontal binning kernel. Figure 10c,d show brightness enhanced images of Figure 10b using Kim’s and Jiang’s algorithms, respectively. Figure 10f shows the brightness-enhanced image of Figure 10b using the proposed algorithm with a maximum binning ratio of 4. For clearer visual comparison, the magnified versions of Figure 10 are shown in Figure 11.


Low-Light Image Enhancement Using Adaptive Digital Pixel Binning.

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

The magnified version of the red box shown in Figure 10a: (a) The reference image with 18 dB gain; (b) underexposed image with 12 dB gain; (c) enhanced image of (b) using 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 algorithm.
© Copyright Policy
Related In: Results  -  Collection

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

sensors-15-14917-f011: The magnified version of the red box shown in Figure 10a: (a) The reference image with 18 dB gain; (b) underexposed image with 12 dB gain; (c) enhanced image of (b) using 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 algorithm.
Mentions: Figure 10a,b respectively show 18 dB and 12 dB AFE gain images. Figure 10c shows the brightness-enhanced image of Figure 10b using the ordinary digital pixel binning with the horizontal binning kernel. Figure 10c,d show brightness enhanced images of Figure 10b using Kim’s and Jiang’s algorithms, respectively. Figure 10f shows the brightness-enhanced image of Figure 10b using the proposed algorithm with a maximum binning ratio of 4. For clearer visual comparison, the magnified versions of Figure 10 are shown in Figure 11.

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.