• The KIPS Transactions:PartA
• /
• v.16A no.6
• /
• pp.473-480
• /
• 2009

This paper is to enhance a color image running in the PXA255 ARM processor based on embedded linux environments. Retinex is one of the representative algorithm for image enhancement in the previous research. However, retinex is not suitable the run on the embedded system because of its long processing time. So, we proposed the image enhancement algorithm for embedded system, with less quantity of operation and the effect equivalent to retinex. To achieve this goal, we propose and implement the image enhancement algorithm, which utilizes the image formation model and gamma correction to be effective in a back-light and dark image. The proposed algorithm converts the color space from RGB to HSV, and then V and S channels are processed. In order to optimize the proposed method in the PXA255 ARM processor, quantity of calculation is reduced. The performance of the proposed algorithm was evaluated through qualitative method and quantitative method. The results show that brightness and contrast are improved with less quantity of operation.

• Proceedings of the IEEK Conference
• /
• summer
• /
• pp.122-127
• /
• 2004

The color gamut mapping method that is used for enhancing the color reproduction quality between PC monitor and printer devices is adopted for display quality enhancement. The high definition display devices operate at the clock speed of around $70\;MHz\;\sim\;150\;MHz$ and permit several nano seconds for real-time processing. Thus, the concept of three-dimensional reduced resolution look-up table is used. The required hardware can be greatly reduced by look-up table resolution adjustment. The proposed hardware architecture is successfully implemented in ASIC and also successfully adopted in display quality enhancement purposes.

• Journal of Information Processing Systems
• /
• v.9 no.1
• /
• pp.141-156
• /
• 2013

In this paper we propose a method to detect human faces in color images. Many existing systems use a window-based classifier that scans the entire image for the presence of the human face and such systems suffers from scale variation, pose variation, illumination changes, etc. Here, we propose a lighting insensitive face detection method based upon the edge and skin tone information of the input color image. First, image enhancement is performed, especially if the image is acquired from an unconstrained illumination condition. Next, skin segmentation in YCbCr and RGB space is conducted. The result of skin segmentation is refined using the skin tone percentage index method. The edges of the input image are combined with the skin tone image to separate all non-face regions from candidate faces. Candidate verification using primitive shape features of the face is applied to decide which of the candidate regions corresponds to a face. The advantage of the proposed method is that it can detect faces that are of different sizes, in different poses, and that are making different expressions under unconstrained illumination conditions.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.9 no.2
• /
• pp.103-113
• /
• 1991

The accuracy of input coordinates of ground control points and check points affects great influences to the results of ground coordinate computation in using SPOT digital image data. The original SPOT images displayed on CRT are not usually adequate for identifying the object features and determining the point positioning. Hence, appropriate image processing techniques such as contrast enhancement, subpixel interpolation, edge enhancement, and spatial filtering are needed. In this study, the principles of digital image processing needed for accurate three dimensional positioning and spectral characteristic analysis are investigated. The algorithms for the actual applications are developed and programmed. And using the developed image processing software, some SPOT P-mode and XS-mode images are merged into the SPOT P＋XS, the high-resolution color composite image.

• Journal of Broadcast Engineering
• /
• v.13 no.5
• /
• pp.651-661
• /
• 2008

This paper proposes a novel contrast enhancement (CE) algorithm for color images using the modified error diffusion (ED). After conventional color histogram equalization (HE), artifacts such as false contours are produced in the contrast enhanced image. The proposed CE algorithm using the modified ED consists of two parts: CE and ED. In the first part, a low-contrast input image is enhanced by the conventional HE method. In the second part, we use the modified ED algorithm. The inputs of the second part are the average and scaled difference images of the original color input image and the HE image, in which the scaled color difference image is diffused by the ED algorithm. In the proposed algorithm, the modified ED algorithm reduces the artifacts produced in the HE image, and increases the number of color levels. Computer simulations with a number of low-contrast color images show the effectiveness of the proposed CE method in terms of the visual quality as well as the probability mass function. It can be used as a post-processing for CE with simultaneous artifact reduction in various display devices.

• Journal of IKEEE
• /
• v.22 no.4
• /
• pp.1188-1194
• /
• 2018

This paper proposes an image enhancement-based license plate detection algorithm to improve the overall performance of system. Non-uniform illumination conditions have huge impact on overall plate detection system accuracy. In this paper, we propose an algorithm for color image enhancement-based license plate detection for improving accuracy of images degraded by excessively strong and low sunlight. Firstly, the image is enhanced by Multi-Scale Retinex algorithm. Secondly, a plate detection method is employed to take advantage of geometric properties of connected components, which can significantly reduce the undesired plate regions. Finally, intersection over union method is applied for detecting the accurate location of number plate. Experimental results show that the proposed method significantly improves the accuracy of plate detection system.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.17 no.8
• /
• pp.2068-2082
• /
• 2023

With the rapid development of deep learning, Depth Map Super-Resolution (DMSR) method has achieved more advanced performances. However, when the upsampling rate is very large, it is difficult to capture the structural consistency between color features and depth features by these DMSR methods. Therefore, we propose a color-image guided DMSR method based on iterative depth feature enhancement. Considering the feature difference between high-quality color features and low-quality depth features, we propose to decompose the depth features into High-Frequency (HF) and Low-Frequency (LF) components. Due to structural homogeneity of depth HF components and HF color features, only HF color features are used to enhance the depth HF features without using the LF color features. Before the HF and LF depth feature decomposition, the LF component of the previous depth decomposition and the updated HF component are combined together. After decomposing and reorganizing recursively-updated features, we combine all the depth LF features with the final updated depth HF features to obtain the enhanced-depth features. Next, the enhanced-depth features are input into the multistage depth map fusion reconstruction block, in which the cross enhancement module is introduced into the reconstruction block to fully mine the spatial correlation of depth map by interleaving various features between different convolution groups. Experimental results can show that the two objective assessments of root mean square error and mean absolute deviation of the proposed method are superior to those of many latest DMSR methods.

• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 2009.01a
• /
• pp.334-336
• /
• 2009

Estimation and correction of color temperature of digital images are basis of white balance adjustment after image acquisition stage. White balance is one of the most important image processing techniques for subjective image quality enhancement. Correction of color temperature is applied for white balance adjustment or for changing the mood of a picture. A picture taken under the daylight can be changed to have a mood of sunset or cloudy day, for example. We evaluate color temperature transformation of high dynamic range images in linear and log domain, and we conclude that linear domain transformation shows better results.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.53 no.10
• /
• pp.77-83
• /
• 2016

This paper presents an adaptive retinex algorithm using skewness for contrast enhancement of color images. In order to estimate the degree of low contrast of an image, skewness of luminance of an observed image is used to define a parameter, and a non-linear function is proposed to compensate the reflectance using the parameter and estimated reflectance. In addition, determination of gain and offset of the non-linear function is addressed using statistics of the estimated reflectance. The relation between an observed luminance and the compensated luminance is used to compensate color components with the reduction of computational cost. The experimental results show that the proposed algorithm has the capability to effectively improve the contrast without color distortion.

• Journal of Korea Multimedia Society
• /
• v.9 no.11
• /
• pp.1455-1464
• /
• 2006

In this paper, we propose an adaptive image enhancement algorithm. The proposed algorithm is classified with the MIE technique for intensity enhancement of input image and MSE techniques for saturation enhancement. The MIE technique is proposed to control the gamut mapping problem and a sudden change in image-brightness while Luminance signal is processing, The MSE techniques are proposed to control de-saturation or over-saturation while chrominance signal is processing. The proposed algorithm is focused on processing preference color for human vision in order to generate better image quality than the algorithms focused on processing uniformly to whole images, This algorithm can be applied to a monitor, TV and other display devices for high quality image.