Joonyoung Chang

Correction of Axial and Lateral Chromatic Aberration With False Color Filtering

In this paper, we propose a chromatic aberration (CA) correction algorithm based on a false color filtering technique. In general, CA produces color distortions called color fringes near the contrasting edges of captured images, and these distortions cause false color artifacts. In the proposed method, a false color filtering technique is used to filter out the false color components from the chroma-signals of the input image. The filtering process is performed with the adaptive weights obtained from both the gradient and color differences, and the weights are designed to reduce the various types of color fringes regardless of the colors of the artifacts. Moreover, as preprocessors of the filtering process, a transient improvement (TI) technique is applied to enhance the slow transitions of the red and blue channels that are blurred by the CA. The TI process improves the filtering performance by narrowing the false color regions before the filtering process when severe color fringes (typically purple fringes) occur widely. Last, the CA-corrected chroma-signal is combined with the TI chroma-signal to avoid incorrect color adjustment. The experimental results show that the proposed method substantially reduces the CA artifacts and provides natural-looking replacement colors, while it avoids incorrect color adjustment.

Adaptive Arbitration of Intra-Field and Motion Compensation Methods for De-Interlacing

De-interlacing based on motion compensation (MC) is one of the best ways of improving the resolution of a progressive video converted from an interlaced source. However, the converted frames often suffer from serious defects like feathering artifacts in regions with inaccurate motion vectors (MVs). In such regions, an intra-field method that is robust to MV errors can be used to correct motion compensation artifacts (MCAs). In this letter, we propose an adaptive arbitration method to combine intra-field and MC methods adequately. The proposed method considers the reliability of MC results along with the MV reliability measured by the spatio-temporal consistency of MVs and displaced pixel differences. The MC reliability is determined by detecting MCAs in MC results, and then the MV reliability is adjusted according to the MC reliability. Also, adaptive-weight MC and pseudo MC methods are proposed to provide more reliable MC results and to improve the accuracy of MCA detection, respectively. Experimental results show that the proposed method provides high-quality video sequences while reducing many visible artifacts.

Partial differential equation–based approach for removal of chromatic aberration with local characteristics

We propose a chromatic aberration (CA) reduction technique that removes artifacts caused by lateral CA and longitudinal CA, simultaneously. In general, most visible CA-related artifacts appear locally in the neighborhoods of strong edges. Because these artifacts usually have local characteristics, they cannot be removed well by regular global warping methods. Therefore, we designed a nonlinear partial differential equation (PDE) in which the local characteristics of the CA are taken into account. The proposed algorithm estimates the regions with apparent CA artifacts and the ratios of the magnitudes between the color channels. Using this information, the proposed PDE matches the gradients of the edges in the red and blue channels to the gradient in the green channel, which results in an alignment of the positions of the edges while simultaneously performing a deblurring process on the edges. Experimental results show that the proposed method can effectively remove even significant CA artifacts, such as purple fringing as identified by the image sensor. The experimental results show that the proposed algorithm achieves better performance than existing algorithms.

Interlaced-to-progressive conversion using adaptive projection-based global and representative local motion estimation

We propose a motion-compensation-based deinterlacing algorithm using global and representative local motion estimation. The proposed algorithm first divides an entire image into five regions of interest (ROIs) according to the temporally predicted motion type (i.e., global or local) and the spatial position. One of them is for global motion estimation and the others are for local motion estimation. Then, dominant motions of respective ROIs are found by adaptive projection approach. The adaptive projection method not only estimates dominant local motions with low computational cost, but also ensures consistent global motion estimation. Using the estimated motion vectors, adaptive two-field bidirectional motion compensation is performed. The arbitration rules, measuring the reliability of motion compensation accurately, produce high-quality deinterlaced frames by effectively combining the results of motion compensation and the stable intrafield deinterlacing. Experimental results show that the proposed deinterlacing algorithm provides better image quality than the existing algorithms in both subjective and objective measures.

Color transient improvement for signals with a bandlimited chrominance component

In color television broadcasting standards, such as National Television System Committee (NTSC) and phase alteration line (PAL), the bandwidth of the chrominance signals are even narrower than those of the luminance signals. Also in digital video standards, the chrominance signals are usually low-pass filtered and subsampled to reduce the amount of data. Because of these reasons, the chrominance signals have poor transition characteristics and the slow transition causes blurred color edges. A color transient improvement algorithm is proposed by exploiting the high-frequency information of the luminance signal. The high-frequency component extracted from the luminance signal is modified by adaptive gains and added to the low-resolution chrominance signals in the proposed algorithm. The gain is estimated to minimize the l2 norm of the error between the original and the estimated pixel values in a local window. The proposed algorithm naturally improves the transient of the chrominance signal as much as that of the luminance signal without overshoots and undershoots. The experimental results show that the proposed method produces steep and natural color edge transition and reconstructs narrow line edges that are not restored by the conventional algorithms.

Kernel-based image upscaling method with shooting artifact reduction

This paper describes the interpolation algorithm which contains shooting or ringing artifact suppression based on windowed sinc interpolator. In general, the windowed sinc interpolator can achieve better performance by using wider window. However, using wide window causes more ripples that produce unwanted defects such as ringing or shooting artifact. Therefore, shooting reduction technique is proposed in this paper for using wider windows to improve the performance without shooting artifact. The proposed algorithm can suppress shooting artifact by using median sinc interpolator and it can be also used as a post processor for many kernel-based interpolation methods. The resulted image shows that the proposed algorithm can maintain local details and suppress shooting artifact in the image well.

Global motion-compensated preprocessing algorithm for block-based frame-rate conversion

We propose a global motion (GM) compensated preprocessing algorithm for block-based frame rate conversion (FRC). The proposed method estimates camera motions such as zooms or rotations between two input frames, and accordingly, produces nontranslational GM-free pictures by performing GM compensation with respect to the temporal location where the FRC method reconstructs an intermediate frame. To reduce the computational load, the proposed method first subsamples input images, and then block-wise motion estimation (ME) is performed. With the ME results, the proposed method detects scene changes and nontranslational GMs. This allows us to determine whether to proceed with the GM estimation and compensation processes. The geometric motion model is adopted to describe camera motions with four parameters, and these values are iteratively found on a motion vector (MV) field. Experimental results show that the proposed algorithm achieves significant performance improvements of subsequent FRC methods.

Frame-rate conversion using hybrid-search-based motion estimation and adaptive motion-compensated interpolation

We propose a frame-rate conversion algorithm using hybrid-search-based motion estimation (ME) and adaptive motion-compensated interpolation (MCI). The ME method uses three search strategies: recursive search, three-step search with predictions, and single predicted search. One of them, which is best suited for the predicted motion type, is adaptively performed on a block basis. This adaptation process improves the accuracy of the estimated motion vectors without increasing the computational load. With the estimated motion vectors, the proposed MCI method reconstructs high-quality frames, without producing block artifacts, by considering multiple motion trajectories. The method utilizes pixel smoothness constraints besides motion-vector reliability when creating and combining the multiple motion-compensated results to remove block artifacts in regions with unreliable motion vectors. Experimental results show that the proposed ME method produces reliable motion vectors that are closer to true motions. Also, the proposed MCI method achieves better image quality than existing algorithms.

Video resampling algorithm for simultaneous deinterlacing and image upscaling with reduced jagged edge artifacts

In this paper, we propose a video resampling method for simultaneous deinterlacing and image upscaling. The proposed method is composed of two steps: the initial image magnification step and the edge enhancement step. In order to convert an interlaced image into a display format image, a filtering strategy, which resizes images with arbitrary ratios and reduces the overall computational load, is performed region adaptively using local characteristics such as motion or motionless regions. After the initial step, the proposed jagged edge correction (JEC) method is applied to the initially upscaled images to correct the stair-like artifacts (jagged edges) which are caused by ignoring any edge information in diagonal edge regions during the linear filtering process. Moreover, this method can be very useful for various upscaling applications to improve edge quality since it can be used in combination with other common interpolation techniques, such as cubic spline techniques. Experimental results show that the proposed method substantially reduces the jagged edges of the converted images and provides steep and natural-looking edge transitions.

Color rolling suppression algorithm considering luminance and color constancy

When a digital image sequence is sampled with a periodically emitting light source, the color rolling (CR) phenomenon occurs, which is shown by periodical variations of color and luminance values. In conventional CR suppression (CRS) methods, color variation has been reduced by using auto white balance methods. However, the CR phenomenon still appears in the resulting image sequences due to interfield illuminant intensity variation. In the proposed CRS method, the interfield luminance and color variations are simultaneously suppressed by estimating the illuminant change between the current and the target fields. In order to consider the object motions, a motion detection technique is used to estimate the luminance changes that occurred due to the CR phenomenon. Moreover, the illuminant color is estimated using the CR achromatic color distribution in the chromaticity space which is founded on the periodicity of the CR phenomenon. Based on the motion detection and the achromatic color detection techniques, the illuminant is estimated using the obtained color components in a common area of both static and achromatic regions. The experimental results demonstrate that our strategy efficiently suppresses the CR phenomenon without being affected by moving objects and produces luminance and color constant image sequences.