• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.2
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• pp.344-349
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• 2012

This paper describes experimental results and their analysis on the new test images, called as the McMaster image dataset, to develop demosaicking techniques. The well-known image dataset for demosaicking is so far the Kodak image dataset. However, different results have been reported, as the new image dataset is engaged in developing demosaicking techniques. Thus, we conduct a series of experiments on both the McMaster dataset and the Kodak dataset; we analyze and compare those experimental results; and we provide the peculiar features of the new dataset. Also, the experimental results and their analysis indicate that the McMaster dataset deserves to be a test image dataset for future demosaicking techniques; thus, we expect they can be utilized as basic data for demosaicking.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.5C
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• pp.286-294
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• 2011

In most digital cameras, images are obtained by a sensor overlaid by the color filter array (CFA) such as Bayer, demanding a demosaicking procedure to rebuild the full resolution color images. However, due to the nature of sensor, it is necessary to consider denoising step to remove the noise. In this paper, we analyze demosaicking and denoising jointly and show that the proposed method can solve the denoising issue by simple manner, well suppress different level of noises. The proposed algorithm yields comparable performances measured by several image quality assessment (CPSNR, SCIELAB, and FSIM), while the computational cost is low.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.10
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• pp.1434-1440
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• 2014

This paper describes a demosaicking method for hexagonally-structured color filter array. Demosaicking is essential to acquire color images using color filter array (CFA) in single sensor imaging. Thus, CFA patterns have been discussed in order to improve image quality in single sensor imaging after the Bayer pattern are introduced. Advancements in imaging sensor technology recently introduce a hexagonal CFA pattern. The hexagonal CFA can be considered to be a 45-degree rotational version of the Bayer pattern, thus demosaicking can be implemented by an existing method with backward and forward 45-degree rotations. However, this approach requires heavy computing power and memory in image sensing devices because of the image rotations. To overcome this problem, we proposes a demosaicking method for a hexagonal Bayer CFA without rotations. In addition, we introduce a weighting parameter in our demosaicking method to improve image quality and to unifying exiting method with our method. Experimental results indicate that the proposed method is superior to conventional methods in terms of PSNR. In addition, some optimized values for the weighting parameter are provided experimentally.

• Journal of Broadcast Engineering
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• v.15 no.2
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• pp.265-279
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• 2010

A color image requires at least three color channels to obtain the full color image. However the image sensor obtains only the intensity of the brightness, that is, three image sensors are required for every pixel to capture the full color image. Since the image sensor is quiet expensive, most of digital still cameras adopt single image sensor array with color filter array (CFA) to reduce the size and the cost. Since the image obtained using single sensor array has only one color component per pixel, we need to reconstruct the missing two color components to obtain the full color image. We call this process as color filter interpolation or demosaicking. In this paper, demosaicking algorithm composed of two large step is proposed. Proposed algorithm is combined with several different algorithms such as Edge-directed demosaicking, Second-order gradients as correction terms, Smooth hue transition Interpolation, etc. The simulation results show that the proposed algorithm performs much better than the state-of-the-art demosaicking algorithms in terms of both subjective and objective qualities.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.9
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• pp.1276-1282
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• 2013

This paper presents a demosaicking method based on high-order interpolation with parameters. Demosaicking is an essential process in capturing color images through a single sensor-array. Thus, a lot of methods including the Hamilton-Adams(HA) method has been studied in this literature. However, the image quality depends on various factors such as contrast and correlation in color space; existing algorithms depend on test images in use. Consequently, a new test image set was suggested to develop demosaicking algorithms properly. According to previous studies, the HA method shows high performances with the new test data set. In this paper, we improve the HA method using high-order interpolation with parameters. Also, we provide an analysis and formulations for the proposed method. To evaluate our method, we compare our method with the existing methods both objectively and subjectively. The experimental results indicate that the proposed method is superior to the existing methods.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.4
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• pp.68-74
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• 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
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• v.45 no.3
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• pp.46-54
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• 2008

Most commercial CCD/CMOS image sensors have CFA(Color Filter Array) where each pixel gathers light of a selective color to reduce the sensor size and cost. There are many algorithms proposed to reconstruct the original clolr image by adopting pettern recognition of regularization methods to name a few. However the resulting image still suffer from errors such as flase color, zipper effect. In this paper we propose an adaptive edge weight demosaicking algorithm that is based on POCS(Projection Onto Convex Sets) not only to improve the entire image's PSNR but also to reduce the edge region's errors that affect subjective image quality. As a result, the proposed algorithm reconstruct better quality images especially at the edge region.

• Journal of Information Processing Systems
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• v.16 no.6
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• pp.1479-1494
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• 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 Society of Computer and Information
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• v.22 no.11
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• pp.25-30
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• 2017

In this paper, We proposed an effective demosaicking method for single chip RGB-NIR sensors to recover RGB and NIR images. As the method operates in the spatial frequency domain, the frequency domain characteristics of the sampled CFA data are investigated. Using the luminance signal in the frequency domain and the chrominance signals are processed separately with different filters. The simulated images using the real images are compared with other state-of-art methods. As a result, the proposed demosaicking method resulted an effective calculation by a single processing which the existing alternating projection method requires repeated calculation.

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