- Research Article
- Open Access
Using Adaptive Tone Mapping to Enhance Edge-Preserving Color Image Automatically
© Kuo-Jui Hu et al. 2010
- Received: 14 April 2010
- Accepted: 6 December 2010
- Published: 14 December 2010
One common characteristic of most high-contrast images is the coexistence of dark shadows and bright light source in one scene. It is very difficult to present details in both dark and bright areas simultaneously on most display devices. In order to resolve this problem, a new method utilizing bilateral filter combined with adaptive tone-mapping method is proposed to improve image quality. First of all, bilateral filter is used to decompose image into two layers: large-scale layer and detail layer. Then, the large-scale layer image is divided into three regions: bright, mid-tone, and dark region. Finally, an appropriate tone-mapping method is chosen to process each region according to its individual property. Only large-scale layer image is enhanced by using adaptive tone mapping; therefore, the details of the original image can be preserved. The experiment results demonstrate the success of proposed method. Furthermore, the proposed method can also avoid posterization produced by methods using histogram equalization.
- Dark Region
- Histogram Equalization
- Bright Region
- Bilateral Filter
- Gamma Correction
Human eyes can capture a very wide dynamic range of 10-order of magnitude through brightness adaptation. In other words, due to the existence of rods and cones in our retina, human visual system can accommodate the large variation by changing between scotopic vision and photopic vision. However, typical CMOS or CCD sensors can only capture a range of thousands in magnitude; typical displays in normal viewing conditions and printing media can only reproduce information over a range of just a few hundreds or less. As a result, even though humans can recognize the details clearly in both dark and bright regions in a scene, the image captured by digital camera may be either too dark or too bright to present details. This is due to the limited dynamic range of the digital camera. Hence, some image-processing techniques must be utilized to enhance these images.
Recently, high dynamic range (HDR) image processing is gaining its popularity. HDR tone-mapping techniques have been developed to compress the dynamic range of the image for displaying on prevalent monitors, which the dynamic range is often smaller. The tone-mapping operators for HDR image can be roughly classified into four categories: global operators [2, 3], local operators , frequency domain operators , and gradient domain operators . These methods all require at least two images with different exposure levels to produce one HDR image. In some cases, it is not possible to obtain two different exposed images.
Lately, an automatic image enhancement algorithm for low dynamic range images is introduced by Wu . The algorithm is able to lighten dark regions while retaining the details of bright regions. The principle behind the algorithm is that an image can be decomposed into a large-scale layer and a detail layer by using bilateral filtering. By applying histogram equalization only to the large-scale layer, details of the images can be preserved. However, due to the nature of histogram equalization, the algorithm still suffers from the phenomena of posterization. The effect is shown in Figure 1(d).
Cope with both work in  and method introduced by Wu  inspire the proposed one. The same bilateral filtering method is used in that work to preserve image details. The improvement in the proposed work is that the large-scale layer image is first divided into three regions according to its histogram, and then according to the individual visual property of each region, appropriate tone-mapping method is chosen to enhance individual region. The experiment results show the proposed method is effective and can avoid posterization.
2.1. Bilateral Filter
2.2. Adaptive Tone Mapping
The large-scale layer can be divided into two classes, the class 1 and class 2, by applying Otsu's thresholding method.
The mapping result of both and carry out the level increasing of the dark region near mid-tone region.
In Figure 6, the solid curve is the mid-tone level distribution generated from Otsu's method recursively, while dotted curve is the mapped regions of both dark region and bright region using (2).
Note that when the two new bounds and are defined, must be shifted from to , and must be shifted from to . This shifting is for gradual change in gray level.
An algorithm based on bilateral filter associated with adaptive tone mapping to effectively enhance images is proposed. From the experimental results demonstrates that the proposed algorithm outperforms and resolves posterization drawbacks as occurred in .
By easing the bilateral filter, the image is decomposed into two layers. The detail layer remains unprocessed so that the details can be retained within the adaptive tone mapped image. The color information is kept unchanged before the large-scale layer is obtained from bilateral filtering allowing the color appearance of input image can be remained. The adaptive tone mapping manipulates different regions according to properties of the corresponding regions, so that global smoothness can be accomplished without losing local details, and global dynamic range can be stretched with achieving promising contrast enhancement. Finally, the gamut volume and color difference using CIE94 color difference equation are calculated to demonstrate the proposed method is capable of producing less color shift while obtaining larger gamut volume than original image. Additionally, the enhancement of color image is effectively performed without requirement of manually parameters setting during the whole process.
Currently, the proposed algorithm is able to cope well with underexposed image or high-contrast image. Some problems still occurred when processing overexposed image, and these issues are under investigating.
The work is supported by MOEA Project no. 8351AA1100 implemented by DTC/ITRI.
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