In a low-illumination environment

such as in nighttime video surveillance and some special scenes

the limitations of the image acquisition device

non-professional photography

and loss of information in video transmission often results in the acquisition of image with low brightness and poor contrast.Such conditions bring great challenges to image post-processing

such as image recognition

segmentation

and classification.Therefore

enhancing a low-illumination image in the preprocessing step is necessary.The aim of low-illumination image enhancement is to enhance the dark area

suppress the highlighted area

and realize the image clarity.At present

most of the methods are based on Histogram Equalization(HE)

Retinex theory

and homomorphic filtering.Particularly

HE can adaptively improve the dynamic range of the image gray scale but it also can lead to unnatural over-enhancement of image contrast;and the merging gray levels cause loss of some details of the image.Retinex-based algorithms can enhance image contrast to a certain extent

but the computational complexity is generally high

the computational speed is slow

and the image color is also easily distorted.The premise of the enhancement algorithm based on homomorphic filter is that the illumination is uniform

so this method is unsuitable for low-illumination images with uneven illumination.Moreover

this method also lacks self-adaptability because the dynamic range depends on the frequency of the filter.Although the logarithmic transform can show more details of the dark area

but it also loses some details of the bright region.The Retinex algorithm and the enhancement algorithm based on homomorphic filter all involve logarithmic transformation

but none of the logarithmic base are specified.Only one-way logarithmic transformation is carried out

which can only improve the image contrast of the dark area.To overcome the shortcomings of the existing algorithms

and inspired by the characteristics of logarithmic transformation

this paper proposes a low-illumination image enhancement algorithm based on adaptive bilateral logarithm transformation with bandwidth preserving. The proposed method includes four steps.First

the low-illumination image is transformed into a standardized image by a special gray transformation called the standard transformation

which can stretch the image contrast to some extent.The purpose of image standard transformation is to make the image gray/color spectrum width equal to 256 to preserve full bandwidth.Compared with non-standardized image

the contrast and brightness of standardized image had increased.Standard transformation lays foundation for further image quality optimization.The second step of the algorithm is computation of the Average Luminance(AL) of the standardized image.Then

the adaptive bilateral logarithm transformation with preserved bandwidth is performed according to AL.More concretely

if AL is less than 127.5

reverse logarithm transformation with bandwidth preserving is carried out first

and then the forward logarithm transformation with bandwidth preserving is performed.Otherwise

forward logarithm transformation with bandwidth preserving is carried out

and then the reverse logarithm transformation with bandwidth preserving is performed.Through calculation

the value of logarithmic base is set to 1.021 983 956 89

thus achieving logarithm transformation with bandwidth preserving.Through this step

image details both in dark area and bright area can be displayed.Finally

the image is rounded out to obtain the enhanced image. In the experiment

29 high-quality images in the LIVE database release 2 are used as reference images

and then processed into low-illumination images by Photoshop CS5.After that

the proposed algorithm is utilized to enhance these low-illumination images and compared with the enhanced results obtained by HE

Multi-scale Retinex(MSR)

and Natural Preserved Enhancement Algorithm(NPEA).Qualitative and quantitative analyses are conducted to evaluate the proposed algorithm.Experimental results show that the overall contrast and brightness of the proposed method are improved subjectively

and the enhancement effect is better compared with the other three enhancement algorithms.Simultaneously

the Peak Signal-to-Noise Ratio(PSNR) and Structure Similarity(SSIM) value obtained by the proposed method is higher than the other three algorithms.The average PSNR and SSIM values obtained by the proposed method is 22.75 dB and 0.86

whereas the average PSNR and SSIM value of the other three method are 16.16 dB and 0.58(HE)

15.82 dB

and 0.62(MSR)

18.62 dB

and 0.78(NPEA)

respectively.In addition

the average running time of the proposed algorithm is relatively short(74 ms);however

the running time of MSR and NPEA are respectively 11.28 s and 11.58 s under the same conditions. The proposed method makes up for the defects of retinex algorithm and homomorphic filtering method

which can improve the dark area and bright area contrast of the image at the same time.Consequently

it can enhance the low-illumination image effectively.Moreover

the algorithm can eliminate the halo artifact caused by Retinex

and it does not merge gray levels as HE.The enhanced image is more natural and more consistent with the human visual system.Meanwhile

the proposed algorithm is simple and easy to implement

which can greatly improve the operational efficiency.The proposed method can be widely applied to image enhancement in low-illumination environment under backlight or uneven illumination.However

the limitation of the proposed algorithm is the contrast and brightness of the enhanced image should be further improved.The future work will focus on applying the average luminance transformation to the enhanced image to do further enhancement.In addition

for the sake of further improving the robustness of the algorithm

more tests and verification are required for the nighttime video monitoring field.