A color image enhancement algorithm based on quaternion representation of vector rotation

Author(s):  
Fangnian Lang ◽  
Jiliu Zhou ◽  
Yuan Yan Tang ◽  
Zhaowei Shang

Detail enhancement of color images is required in many applications. Unsharp masking (UM) is the most classical tool for detail enhancement. Many generalizing UM approaches have been proposed, for example, the rational UM technique, the cubic unsharp technique, the adaptive UM technique and so on. For color images, these algorithms have three steps: (a) Implement the color2gray step; (b) design an extracting method of high frequency information (HFI) based on the luminance component (LC); (c) complete the enhancing process utilizing the HFI. However, using only the HFI of the LC may lose the HFI of the chrominance component (CC). This paper proposes a quaternion based detail enhancement algorithm to extract details of the color image using both of the luminance and CCs. The proposed algorithm is designed to address three tasks: (1) designing an extraction method of the color high frequency information (CHFI) based on quaternion description of the 3D vector rotation; (2) performing an effective fusion strategy of the CHFI and the gray high frequency information (GHFI); (3) designing a quaternion based measure method of the local dynamic range, based on which the enhancement coefficients of the proposed algorithm can be determined. The performance of the proposed algorithm compares favorably with many other similar enhancement algorithms. The eight parameters can be adjusted to control the sharpness to produce the desired results, which makes the proposed algorithm practically useful.

2013 ◽  
Vol 321-324 ◽  
pp. 1133-1137
Author(s):  
Yu Ting Song ◽  
Xiu Hua Ji ◽  
Shi Lin Zhao

This paper proposes an improved color image enhancement algorithm based on 3-D color histogram equalization algorithm. When the existed 3-D color histogram equalization algorithms in the literatures are applied in processing dim color images, the processed color images often turn pale due to the decrease of color-saturations and have false contours due to gray-scale merging phenomenon in the histogram equalization algorithm. In this paper, the proposed algorithm can make more pixels of the processed color images keep their color-saturations and reduce the gray-scale merging with Logarithmic histogram equalization algorithm. Test results with dim color images present a better effect of image enhancement.


2013 ◽  
Vol 427-429 ◽  
pp. 1813-1816 ◽  
Author(s):  
Ting Ting Liu ◽  
Ya Dong Jiang ◽  
Wei Yi Ding ◽  
Xiang Sheng Meng ◽  
Xian Wang

Infrared images have the high dynamic range characteristic, generally digitized to 14 bit. While most display devices can only show 8 bit images, so high bit-wide infrared image signal should be compressed to low bit-wide display data without losing the important detail information. A new high-dynamic-range compression and detail enhancement algorithm for infrared images is presented in this paper. In the proposed algorithm, the original infrared image is separated into the low-frequency base component and the high-frequency detail component. Then the base component is compressed with the simple gray level linear mapping, and the detail component is enhanced with the S-curve transformation. Finally, the two components are combined to get the 8 bit enhanced image. The experimental results show that the proposed algorithm can achieve the dynamic range compression while effectively preserve and enhance the local detail information.


2013 ◽  
Vol 397-400 ◽  
pp. 1500-1505
Author(s):  
Jie Xiong ◽  
Lei Lu

When a true color image is enhanced, the same hue should be kept and the useful details should be strengthened in the image enhanced. According to the imaging principle, wavelet illumination-reflection method is proposed. Firstly, true color image is transformed from RGB space to HSV space. Secondly, the saturation is attenuated by CLAHE. Thirdly, the value is decomposed into illumination and reflection by wavelet illumination-reflection model. The details of the reflection are strengthened. The dynamic range of the illumination is reduced in order to enhance the image. Experiments and analysis show that the enhancement algorithm based on wavelet illumination-reflection model is obviously better than multi-scales Retinexs with color restoration (MSRCR).


2013 ◽  
Vol 712-715 ◽  
pp. 2336-2340
Author(s):  
Chuan Bo Huang ◽  
Zi Ping Zhou

In order to get texture features of color image, we proposed a new algorithm which is adapted to extract the texture features for color images in this paper. Firstly, the proposed method adopt quaternion to color image processing that can represent the color image in a holistic manner and parallel processing the R, G and B components. Secondly, we can obtain the directional information and texture features by Quaternion Gabor Filter. The experimental results show that texture feature obtained by our method has good the discrimination power and classifing performance.


Sensors ◽  
2020 ◽  
Vol 20 (6) ◽  
pp. 1560
Author(s):  
Ruijin Chen ◽  
Wei Gao

We designed an end-to-end dual-branch residual network architecture that inputs a low-resolution (LR) depth map and a corresponding high-resolution (HR) color image separately into the two branches, and outputs an HR depth map through a multi-scale, channel-wise feature extraction, interaction, and upsampling. Each branch of this network contains several residual levels at different scales, and each level comprises multiple residual groups composed of several residual blocks. A short-skip connection in every residual block and a long-skip connection in each residual group or level allow for low-frequency information to be bypassed while the main network focuses on learning high-frequency information. High-frequency information learned by each residual block in the color image branch is input into the corresponding residual block in the depth map branch, and this kind of channel-wise feature supplement and fusion can not only help the depth map branch to alleviate blur in details like edges, but also introduce some depth artifacts to feature maps. To avoid the above introduced artifacts, the channel interaction fuses the feature maps using weights referring to the channel attention mechanism. The parallel multi-scale network architecture with channel interaction for feature guidance is the main contribution of our work and experiments show that our proposed method had a better performance in terms of accuracy compared with other methods.


2014 ◽  
Vol 53 (26) ◽  
pp. 6013 ◽  
Author(s):  
Gang Sun ◽  
Songlin Liu ◽  
Weihua Wang ◽  
Zengping Chen

2013 ◽  
Vol 32 (9) ◽  
pp. 2573-2575
Author(s):  
Bing-qing YANG ◽  
Xiao-ping TIAN ◽  
Cheng-mao WU

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