• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2012.05a
• /
• pp.656-659
• /
• 2012

In general, images captured by the color filter array are compressed after applying demosaicking process. Since this process introduces data redundancy which can reduce coding efficiency, several methods have been proposed to address this problem. While some conventional approachs convert color format to GBR or YUV 4:2:2 format, we propose to use the YCoCg 4:2:2 format to carry out compression. The proposed method shows an average bits reduction of 3.91% and PSNR increase of 0.04dB compared with H.264 YUV 4:2:0 intra-profile prediction method.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.54 no.4
• /
• pp.68-74
• /
• 2017

This paper presents a joint demosaicking and arbitrary-ratio down sampling algorithm for color filter array (CFA) images. Color demosaiking is a necessary part of image signal processing pipeline for many types of digital image recording system using single sensor. Also, such as smart phone, obtained high resolution image from image sensor has to be down-sampled to be displayed on the screen. The conventional solution is "Demosaicking first and down sampling later". However, this scheme requires a significant amount of memory and computational cost. Also, artifacts can be introduced or details get damaged during demosaicking and down sampling process. In this paper, we propose a method in which demosaicking and down sampling are working simultaneously. We use inverse mapping of Bayer CFA and then joint demosaicking and down sampling with arbitrary-ratio scheme based on signal decomposition of high and low frequency component in input data. Experimental results show that our proposed algorithm has better image quality performance and much less computational cost than those of conventional solution.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.48 no.3
• /
• pp.62-70
• /
• 2011

Nowadays image sensor is an essential component in many multimedia devices, and it is covered by a color filter array to filter out specific color components at each pixel. We need a certain algorithm to combine those color components reconstructed a full color image from incomplete color samples output from an image sensor, which is called a demosaicking process. Most existing demosaicking algorithms are developed for ideal image sensors, but they do not work well for the practical cases because of dissimilar characteristics of each sensor. In this paper, we propose a new demosaicking algorithm in which the color filter characteristics are fully utilized to generate a good image. To demonstrate significance of our algorithm, we used a commerically available sensor, CBN385B, which is a sort of Honeycomb-style CFA(Color Filter Array) CCD image sensor. As a performance metric of the algorithm, PSNR(Peak Signal to Noise Ratio) and RGB distribution of the output image are used. We first implemented our algorithm in C-language for simulation on various input images. As a result, we could obtain much enhanced images whose PSNR was improved by 4~8 dB compared to the commonly idealized approaches, and we also could remove the inclined red property which was an unique characteristics of the image sensor(CBN385B).Then we implemented it in hardware to overcome its problem of computational complexity which made it operate slow in software. The hardware was verified on Spartan-3E FPGA(Field Programable Gate Array) to give almost the same performance as software, but in much faster execution time. The total logic gate count is 45K, and it handles 25 image frmaes per second.

• Journal of Information Processing Systems
• /
• v.16 no.6
• /
• pp.1479-1494
• /
• 2020

As an important part of image processing, image demosaicking has been widely researched. It is especially necessary to propose an efficient interpolation algorithm with good visual quality and performance. To improve the limitations of residual interpolation (RI), based on RI algorithm, minimalized-Laplacian RI (MLRI), and iterative RI (IRI), this paper focuses on adaptive RI (ARI) and proposes an improved ARI (IARI) algorithm which obtains more distinct R, G, and B colors in the images. The proposed scheme fully considers the brightness information and edge information of the image. Since the ARI algorithm is not completely adaptive, IARI algorithm executes ARI algorithm twice on R and B components according to the directional difference, which surely achieves an adaptive algorithm for all color components. Experimental results show that the improved method has better performance than other four existing methods both in subjective assessment and objective assessment, especially in the complex edge area and color brightness recovery.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.18 no.10
• /
• pp.110-116
• /
• 2017

This paper presents an effective demosaicking algorithm for color filter array (CFA) images acquired from single-sensor devices based on directional interpolation and nonlocal properties of the image. We interpolate the G channel considering diagonal directions as well as horizontal and vertical directions, using a small number of pixels to reflect local properties of the image. Then, we overcome image degradations, such as zipper effects near edges and false colors, by applying nonlocal means (NLM) filtering to the interpolated pixels. R and B channels are reproduced by using directional interpolation with information of the reconstructed G channel and NLM filtering. Experimental results for various McMaster images with high saturation and color changes show that the proposed algorithm accomplishes high PSNR compared with conventional methods. Moreover, the proposed method demonstrates better subjective quality compared with existing methods in terms of reduction of quality degradation, like false colors, and preservation of the image structures, such as edges and textures.

• Journal of Broadcast Engineering
• /
• v.13 no.1
• /
• pp.174-184
• /
• 2008

Complementary color filter array (CCFA) is widely used in consumer-level digital video cameras, since it not only has high sensitivity and good signal-to-noise ratio in low-light condition but also is compatible with the interlaced scanning used in broadcast systems. However, the full-color images obtained from CCFA suffer from the color artifacts such as false color and zipper effects. These artifacts can be removed with edge-adaptive demosaicking (ECD) approaches which are generally used in rrimary color filter array (PCFA). Unfortunately, the unique array pattern of CCFA makes it difficult that CCFA adopts ECD approaches. Therefore, to apply ECD approaches suitable for CCFA to demosaicking is one of the major issues to reconstruct the full-color images. In this paper, we propose a new ECD algorithm for CCFA. To estimate an edge direction precisely and enhance the quality of the reconstructed image, a function of spatial variances is used as a weight, and new color conversion matrices are presented for considering various edge directions. Experimental results indicate that the proposed algorithm outperforms the conventional method with respect to both objective and subjective criteria.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.52 no.7
• /
• pp.77-85
• /
• 2015

In this paper, we present a new method that can detect forged color region using color pattern decomposition and hypothesis testing approach. On the basis of the fact that the variance of the interpolated pixel is smaller than that of the original pixel, we use a statistical test method to judge the statistical inconsistency of variance. For this, we calculate the variance adopting a color pattern decomposition according to the demosaicking pattern. In addition, we apply high-pass filtering to enlarge the difference between the variances of original and interpolated pixel. Through experimental simulations, we can see that our proposed method can effectively detect forged color regions and shows superior detection performance compared to the conventional method.

• Journal of Broadcast Engineering
• /
• v.16 no.3
• /
• pp.561-565
• /
• 2011

This paper presents an imaging system for reconstruction of enhanced color images using the conventional Bayer CFA. By extracting various colors such as RGBCY from two sequential images which consist of a image by broadband G channel lens filter and the other image captured without one, the proposed color image reconstruction system can reduce the computational complexity for demosaicking and make high resolution color information without aliasing artifacts. Because the proposed system uses the common Bayer CFA image sensor, fabricating a new type of CFA is not necessary for obtaining a multi-spectral image, which can be easily extensible for applications of multi-spectral imaging. Finally, in order to verify the performance of the proposed system, experimental results are performed. By comparing with the existing demosaicking methods, the proposed camera system showed the significant improvements in the sense of color resolution.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.51 no.9
• /
• pp.57-66
• /
• 2014

This paper presents a low-complexity barrel distortion correction processor for wide-angle cameras. The proposed processor performs the barrel distortion correction jointly with the color demosaicking, so that the hardware complexity can be reduced significantly. In addition, to reduce the required memory bandwidth, an efficient memory interface is proposed by utilizing the spatial locality of the memory access in the correction process. The proposed processor is implemented with 35K logic gates in a $0.11-{\mu}m$ CMOS process and its correction speed is 150 Mpixels/s at the operating frequency of 606MHz, where the supported frame size is $2048{\times}2048$ and the required memory bandwidth is 1 read/cycle.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.53 no.12
• /
• pp.105-110
• /
• 2016

To reduce the cost and volume of a digital camera, a subsampled color filter array(CFA) image is used and demosaicking is applied to estimate the missing color values. However, aliasing, the overlaps of signals in the frequency domain, occurs when signals are subsampled. This causes aliasing artifacts such as false colors and zipper effects in demosaicking processes. In this paper, the algorithm estimating high-quality color images by removing aliasing artifacts in them is proposed. The aliasing region map is estimated using the sub-sampled signals of the CFA image. By using the aliasing region map and the estimated luminance image, the least squares problem of the observation models is designed and aliasing artifacts are eliminated. The experiments demonstrate that the proposed algorithm restores color images without aliasing artifacts.