Jong Woo Han

Motion-Compensated Frame Interpolation Using Bilateral Motion Estimation and Adaptive Overlapped Block Motion Compensation

In this work, we develop a new motion-compe (MC) interpolation algorithm to enhance the temporal resolution of video sequences. First, we propose the bilateral motion estimation scheme to obtain the motion field of an interpolated frame without yielding the hole and overlapping problems. Then, we partition a frame into several object regions by clustering motion vectors. We apply the variable-size block MC (VS-BMC) algorithm to object boundaries in order to reconstruct edge information with a higher quality. Finally, we use the adaptive overlapped block MC (OBMC), which adjusts the coefficients of overlapped windows based on the reliabilities of neighboring motion vectors. The adaptive OBMC (AOBMC) can overcome the limitations of the conventional OBMC, such as over-smoothing and poor de-blocking. Experimental results show that the proposed algorithm provides a better image quality than conventional methods both objectively and subjectively

A novel image interpolation method using the bilateral filter

In general, since the noise deteriorates the interpolation performance in digital images, it is effective to employ denoising prior to the interpolation. In this paper, we propose a novel interpolation framework in which denoising and image sharpening methods are embedded. In the proposed framework, the image is first decomposed using the bilateral filter into the detail and base layers which represent the small and large scale features, respectively. The detail layer is adaptively smoothed to suppress the noise before interpolation and an edge-preserving interpolation method is applied to both layers. Finally, the high resolution image is obtained by combining the base and detail layers. Experimental results show that the proposed algorithm outperforms the conventional methods while suppressing blurring and jagging.

Vector quantizer based block truncation coding for color image compression in LCD overdrive

The overdrive technique has been popularly used to alleviate the motion blur on liquid-crystal display (LCD) by shortening the response time of the liquid crystal. However, this technique requires a large frame buffer to store the previous frame as a reference. In this paper, we propose a novel block truncation coding based on the vector quantizer for the color image compression in LCD overdrive. Due to the constant output bit-rate and the low computational complexity, the proposed method is suitable for the hardware implementation in LCD overdrive. Experimental results show that the proposed method achieves higher compression ratio as well as better visual quality as compared with the conventional methods.

Frame rate up-conversion using perspective transform

In this paper, we propose a frame rate up-conversion (FRUC) algorithm to increase the temporal resolution of video sequences at the decoder side. First, the proposed algorithm segments a frame into several objects. Then, perspective transforms are used to motion-compensate each object, while the translational block matching algorithm (BMA) is applied to the background. Furthermore, the overlapped block motion compensation (OBMC) technique is used to reduce blocking artifacts in boundary blocks. Experimental results show that the proposed algorithm provides better performance than the conventional approach.

Wavelet based seam carving for content-aware image resizing

In this paper, a novel content-aware image resizing method based on wavelet analysis is proposed. We estimate the local energy map of an image by weighing its multiscale subbands appropriately. Based on the energy map, the image is resized by repeatedly carving out or inserting in a connected path of pixels which is least significant in terms of the energy. Since wavelet analysis is similar to the way the human visual system operates, the obtained energy map reflects human perception with fidelity, and thus, the semantic information in the image can be preserved faithfully in the resizing process. The experimental results show that the proposed method produces higher subjective quality images than scaling and conventional content-aware image resizing techniques.

A novel training based auto-focus for mobile-phone cameras

In this paper, we propose a fast and accurate training based auto-focus (AF) method for mobile-phone cameras. Given a set of training data, the proposed method collects feature vectors consisting of focus value increment ratio. The representative feature vectors corresponding to every possible best in-focus lens position (BILP) are stored in the database. In the proposed training based AF method, the BILP is obtained by comparing the input feature vector with the representative feature vectors in the database. To further enhance the accuracy of the proposed AF method, we also introduce a new focusing window that is effective in detecting the target object. The experimental results show that the proposed method can accurately estimate the BILP faster than the existing methods.

Improved seam carving using a modified energy function based on wavelet decomposition

In this paper, a novel content-aware image resizing technique, perceptually improved seam carving with modified energy function, is proposed. The conventional seam carving method using a gradient-based energy function may cause distortion of deformed object shape depending on the layout and amount of contents. However, the proposed method preserves content shape with high fidelity by exploiting a wavelet-based energy function which represents image features effectively within the scale-space framework. To prevent excessively distorting the images, a switching scheme between seam carving and resampling is proposed based on the energy distribution. Experimental results show that the proposed method can achieve higher subjective image quality than the existing methods including scaling and conventional seam carving.

Edge-oriented two-step interpolation based on training set

Preserving the sharpness of edge structures is highly challenging to image interpolation. In this paper, we propose an edge-oriented two-step interpolation method that utilizes an edge training set. For edge interpolation, the LR edge map is converted into the HR edge map by using the training set. Then, an image is classified into smooth and edge regions using the HR edge map, and both regions are interpolated separately. For edge regions, adaptive edge-oriented interpolation is performed by using the detailed edge structures learned from training. The proposed method is extensively evaluated, and its performance is compared with the conventional edge-based methods. Experimental results show that the proposed method can not only reconstruct the missed edge information by the training set, but also significantly reduce blurring and jagging artifacts around edges by separately interpolating smooth and edge regions.

Irregular-Grid-Overlapped Block Motion Compensation and its Practical Application

In this letter, we present a hybrid motion compensation scheme integrating overlapped block motion compensation (OBMC) and control grid interpolation (CGI), called irregular grid-based OBMC (IG-OBMC). The objective of this letter is to develop both subjectively and objectively improved motion compensation scheme by combining distinct advantages of OBMC and CGI without additional motion vectors or a complicated motion estimation processing. To evaluate the performance, IG-OBMC is applied to error concealment. The simulation results demonstrate that the proposed hybrid motion compensation method achieves a better performance than the conventional motion compensation methods.

A saliency based noise reduction method for Digital TV

In this paper, we propose a content-aware noise reduction (NR) method for the Digital TV, which preserves image textures and edges. In the proposed method, noise is first reduced by a temporal recursive NR filter and then further suppressed by a spatial NR filter. To preserve the image texture, the saliency map which accurately represents edges in a noisy image is employed in the spatial filter. Experimental results show that the proposed method exhibits the better NR performance as compared with conventional methods.