King-Hong Chung

Color Demosaicing Using Variance of Color Differences

This paper presents an adaptive demosaicing algorithm. Missing green samples are first estimated based on the variances of the color differences along different edge directions. The missing red and blue components are then estimated based on the interpolated green plane. This algorithm can effectively preserve the details in texture regions and, at the same time, it can significantly reduce the color artifacts. As compared with the latest demosaicing algorithms, the proposed algorithm produces the best average demosaicing performance both objectively and subjectively

A Lossless Compression Scheme for Bayer Color Filter Array Images

In most digital cameras, Bayer color filter array (CFA) images are captured and demosaicing is generally carried out before compression. Recently, it was found that compression-first schemes outperform the conventional demosaicing-first schemes in terms of output image quality. An efficient prediction-based lossless compression scheme for Bayer CFA images is proposed in this paper. It exploits a context matching technique to rank the neighboring pixels when predicting a pixel, an adaptive color difference estimation scheme to remove the color spectral redundancy when handling red and blue samples, and an adaptive codeword generation technique to adjust the divisor of Rice code for encoding the prediction residues. Simulation results show that the proposed compression scheme can achieve a better compression performance than conventional lossless CFA image coding schemes.

Low-complexity color demosaicing algorithm based on integrated gradients

Color demosaicing is critical for digital cameras, because it converts a Bayer sensor mosaic output to a full color image, which determines the output image quality of the camera. In this work, an efficient decision-based demosaicing method is presented. This method exploits a new edge-sensing measure called integrated gradient (IG) to effectively extract gradient information in both color intensity and color difference domains simultaneously. This measure is reliable and supports full resolution, which allows one to interpolate the missing samples along an appropriate direction and hence directly improves the demosaicing performance. By sharing it in different demosaicing stages to guide the interpolation of various color planes, it guarantees the consistency of the interpolation direction in different color channels and saves the effort required to repeatedly extract gradient information from intermediate interpolation results at different stages. An IG-based green plane enhancement is also proposed to further improve the methods efficiency. Simulation results confirm that the proposed demosaicing method outperforms up-to-date demosaicing methods in terms of output quality at a complexity of around 80 arithmetic operations per pixel.

A Low-Complexity Joint Color Demosaicking and Zooming Algorithm for Digital Camera

This paper presents a low complexity joint color demosaicking and digital zooming algorithm for single-sensor digital cameras. The proposed algorithm directly extracts edge information from raw sensor data for interpolation in both demosaicking and zooming to preserve edge features in its output. This allows the extracted information to be exploited consistently in both stages and also efficiently, as no separate extraction process is required in different stages. The proposed algorithm can produce a zoomed full-color image as well as a zoomed Bayer color filter array image with outstanding performance as compared with conventional approaches which generally combine separate color demosaicking and digital zooming schemes.

A High Performance Lossless Bayer Image Compression Scheme

Demosaicing and compression are generally performed sequentially in most digital cameras. Recent reports show that the compression-first scheme outperforms the conventional demosaicing-first scheme in terms of image quality and complexity. In this paper, an efficient lossless compression scheme for Bayer images is presented. It exploits a context matching technique to rank the neighboring pixels for predicting a pixel. Besides, an adaptive color difference estimation scheme is also proposed to remove the spectral redundancy. Simulation results show that the proposed algorithm can achieve a better compression performance as compared with the existing lossless CFA image coding methods.

Image enlargement using fractal

In fractal coding technique, an image is encoded by making use of its self-similarity property. The image can be reconstructed with some well-defined contractive mappings based on this property and hence, in theory, the reconstructed image can be of any desirable size by using an initial image of appropriate size during the decoding process. However, in practice, the enlarged image is always degraded due to the sub-optimal contractive mappings used. In this paper, a fractal-based image enlargement technique is proposed to reduce this problem. This technique can preserve the details in edge regions while maintaining the smoothness in flat regions, which is superior to conventional image enlargement techniques such as bilinear interpolation and cubic convolution.

An Adaptive Color Filter Array Interpolation Algorithm for Digital Camera

In this paper, an adaptive color filter array (CFA) interpolation method is presented. By examining the edge levels and the variance of color difference along different edge directions, the missing green samples are first estimated. The missing red and blue samples are then estimated based on the interpolated green plane. This algorithm can effectively preserve the details as well as significantly reduce the color artifacts. As compared with some current state-of-art methods, the proposed algorithm provides outperformed results in terms of both subjective and objective image quality measures.

Enhanced integrated gradient and its applications to color demosaicing

In this paper, an effective decision-based demosaicing algorithm for Bayer images is presented. An enhanced edge-sensing measure called enhanced integrated gradient (EIG) is exploited to guide the interpolation along the edges. This measure improves the recently proposed integrated gradient (IG) and hence can support more gradient information from various color intensity and color difference planes under the directional compatibility constraint. An adaptive green plane enhancement which works with the EIG is also proposed to further improve the efficiency of the algorithm.

An Efficient Combined Demosaicing and Zooming Algorithm for Digital Camera

Color demosaicing and digital zooming are common processes in digital cameras and they often employ similar interpolation concepts based on the information extracted from the raw sensor data. Realizing them independently is not efficient as separate extraction processes are required. It may also cause inconsistent utilization of the raw sensor data in different stages. This paper presents a low-complexity combined algorithm which directly extracts edge information from raw sensor data and exploits it consistently and efficiently in both demosaicing and zooming. The proposed algorithm can produce zoomed full-color images and zoomed CFA images with outstanding performance as compared with conventional approaches.

A low-complexity multiscale error diffusion algorithm for digital halftoning

Multiscale error diffusion (MED) digital halftoning technique outperforms classical conventional error diffusion techniques as it can produce a directional-hysteresis-free bi-level image. However, extremely large computation effort is required for its implementation. In this paper, a fast MED-based digital halftoning technique is proposed to produce a halftone image without directional hysteresis at a significantly reduced computational cost. The amount of reduction is monotonic increasing with the image size. For an image of size 512/spl times/512, the proposed algorithm can save 40% of arithmetic operations as compared with MED. Moreover, since it supports parallel processing, processing time can further be squeezed.