Lapped transform‐based codec for frame‐memory reduction in super‐quality LCD overdrive

Abstract— Overdrive is commonly used to reduce the liquid‐crystal response time and motion blur in liquid‐crystal displays (LCDs). However, overdrive requires a large frame memory in order to store the previous frame for reference. In this paper, a lapped transform‐based codec (LTC) is proposed to reduce the frame memory needed for LCD overdrive. In the latest literature, a directional prediction‐based codec (DPC) employs eight directional predictions, which takes up a large percentage of the computational complexity of the codec and does not consider the de‐correlation of the inter‐blocks. Therefore, the LTC first uses the lapped transform to decompose the correlation of the inter‐blocks in the YUV color space. A hadamard transform is then used for energy compaction. The reordered coefficients are pre‐quantized and encoded using the proposed adaptive bit‐plane coding (ABPC) method for a simple hardware implementation. The simulation results show that the proposed LTC significantly improves the DPC in both subjective and objective performance and outperforms the block truncation coding (BTC) and adaptive multi‐level BTC (AM‐BTC), which have been described in the literature.     

A perceived sharpness metric based on the luminance slope and overshoot of the motion‐induced edge‐blur profile

To reduce perceived motion blur on liquid crystal displays, typically various techniques such as overdrive, scanning backlight, black‐data insertion, black‐field insertion, and frame rate up‐conversion are widely employed by the liquid crystal display industry. These techniques aim to steepen the edge transitions by improving the dynamic behavior of the light modulation. However, depending on the implementation, this may result in the perception of irregularly shaped motion‐induced edge‐blur profiles. It is not yet fully understood how these irregularities in the steepened edge‐blur profiles contribute to the perceived sharpness of moving objects. To better understand the consequences of several motion‐blur reduction techniques, a perception experiment is designed to evaluate the perceived sharpness of typical motion‐induced edge‐blur profiles at several contrast levels. Relevant characteristics of these profiles are determined on the basis of the perception results by means of regression analysis. As a result, a sharpness metric with two parameters is established, where one parameter relates to the edge slope and the other to the overshoot/undershoot part of the motion‐induced edge‐blur profile.     

A 6:1 image‐compression method using directional prediction for LCD overdrive

Abstract— An overdrive technology was developed and is widely used to diminish motion blur in LCDs. To store a previous frame in the overdrive operation in a limited‐sized memory, simple image‐compression techniques are required. By considering the strong correlation of nearby pixels in natural images, a new 6:1 color‐image‐compression method based on directional prediction is proposed. Different from the directional prediction of intra‐coding in H.264/AVC, the predictable direction is determined beforehand to minimize the computation complexity. A simple content‐adaptive quantization and bit‐streaming method, which preserves image details and is free from blocking artifacts, is also proposed. The experimental results show that our proposed method outperforms the vector quantization block truncation coding method with an average 3‐dB peak signal‐to‐noise ratio (PSNR) as well as the subjective quality in terms of blocking artifacts.     

HD motion‐picture evaluation method for overdrive technology in the frequency domain

Abstract— In this paper, the development of an advanced level‐adaptive overdrive (A‐LAO) method applicable to a full‐HD LC projector with 1.84 Mpixels, which reduced the gray‐level response time to less than 16 msec, is introduced. In addition, it is shown that a response of less than 8 msec can be achieved by combining the A‐LAO method with a frame interpolation method (120‐Hz refresh). A new motion‐picture evaluation method using frequency‐domain analysis, in other words, perceived bandwidth instead of the conventional time‐domain‐analysis response time evaluation, is reported.     

Advanced level‐adaptive overdrive (ALAO) method applicable to full‐HD LC TVs

Abstract— In this paper, we report on the development of an advanced level‐adaptive overdrive (ALAO) method applicable to full‐HD LC TVs, which makes it possible not only to reduce the gray‐level response time to less than one fourth, but also to improve the S/N ratio for still images by 10 dB; and further to reduce the circuit cost for the LAO method to almost half that of the prior LAO circuit. We have applied the ALAO method to a full‐HD LC front projector with 1.84 Mpixels and a screen size larger than 100 in., and we obtained high‐quality full‐HD moving images.     

Dynamic gamma: Application to LCD motion‐blur reduction

Abstract— A metric, “dynamic gamma,” to quantitatively evaluate the dynamic temporal response of an LCD device is proposed. Dynamic gamma, associated with 2‐D plots, is more suitable for quantitatively characterizing the dynamic characteristics of an LC panel. The dynamic gamma metric was applied to improve the temporal response of LCDs. From dynamic gamma data, overdrive tables can be derived. Dynamic gamma can also be used to evaluate the effectiveness of overdrive. With a second‐order dynamic gamma, the performance of different overdrive algorithms can be quantitatively assessed. The dynamic gamma metric was also applied to backlight flashing and developed a time adaptive overdrive algorithm. The new algorithm reduces the ghosting artifact due to the timing mismatch between LCD driving and backlight flashing. Experimental results from a simulated tracking camera confirms the advantages of the new algorithm designed using dynamic gamma.     

Evaluation of motion performance on scanning‐backlight LCDs

Abstract— The scanning‐backlight technique to improve the motion performance of LCDs is introduced. This technique, however, has some drawbacks such as double edges and color aberration, which may become visible in moving patterns. A method combining accurate measurements of temporal luminance transitions with the simulation of human‐eye tracking and spatiotemporal integration is used to model the motion‐induced profile of an edge moving on a scanning‐backlight LCD‐TV panel that exhibits the two drawbacks mentioned above. The model results are validated with a perception experiment including different refresh rates, and a high correspondence is found between the simulated apparent edge and the one that is perceived during actual motion. Apart from the motion‐induced edge blur, the perception of a moving line or square‐wave grating can also be predicted by the same method starting from the temporal impulse and frame‐sequential response curves, respectively. Motion‐induced image degradation is evaluated for both a scanning‐ and continuous‐backlight mode based on three different characteristics: edge blur, line spreading, and modulation depth of square‐wave grating. The results indicate that the scanning‐backlight mode results in better motion performance.     

Edge‐Optimized À‐Trous Wavelets for Local Contrast Enhancement with Robust Denoising

In this paper we extend the edge‐avoiding à‐trous wavelet transform for local contrast enhancement while avoiding common artifacts such as halos and gradient reversals. We show that this algorithm is a highly efficient and robust tool for image manipulation based on multi‐scale decompositions. It can achieve comparable results to previous high‐quality methods while being orders of magnitude faster and simpler to implement. Our method is much more robust than previously known fast methods by avoiding aliasing and ringing which is achieved by introducing a data‐adaptive edge weight. Operating on multi‐scale, our algorithm can directly include the BayesShrink method for denoising. For moderate noise levels our edge‐optimized technique consistently improves separation of signal and noise.     

Evaluation of liquid‐crystal‐display motion blur with moving‐picture response time and human perception

Abstract— The moving‐picture response time (MPRT) for measuring liquid‐crystal‐display (LCD) motion blur was studied by several organizations in 2001. To determine the LCD motion blur that humans perceive, subjective evaluation experiments using the method of adjustment was conducted to find a strong correlation between perceived motion blur and extended blurred edge time (EBET) of the MPRT measurements. MPRT thus clearly indicates the degree of which humans perceive motion blur.     

Articulated‐Motion‐Aware Sparse Localized Decomposition

Compactly representing time‐varying geometries is an important issue in dynamic geometry processing. This paper proposes a framework of sparse localized decomposition for given animated meshes by analyzing the variation of edge lengths and dihedral angles (LAs) of the meshes. It first computes the length and dihedral angle of each edge for poses and then evaluates the difference (residuals) between the LAs of an arbitrary pose and their counterparts in a reference one. Performing sparse localized decomposition on the residuals yields a set of components which can perfectly capture local motion of articulations. It supports intuitive articulation motion editing through manipulating the blending coefficients of these components. To robustly reconstruct poses from altered LAs, we devise a connection‐map‐based algorithm which consists of two steps of linear optimization. A variety of experiments show that our decomposition is truly localized with respect to rotational motions and outperforms state‐of‐the‐art approaches in precisely capturing local articulated motion.     

Motion‐adaptive alternate gamma drive for flicker‐free motion‐blur reduction in 100/120‐Hz LCD TV

Abstract— LCD motion blur is a well‐known phenomenon, and several approaches have been developed to address it. This includes very‐high‐performance approaches based on motion‐compensated frame rate conversion (MC‐FRC) and very‐low‐cost approaches based on impulsive driving. Impulsive‐driving schemes are attractive because of their low cost, but suffer from two significant issues — loss of luminance and large‐area flicker. A new impulsive‐driving approach using motion‐adaptive alternate gamma driving (MA‐AGD), which removes motion blur and preserves the original luminance level without causing large‐area flicker, is proposed.     

LCD motion‐blur estimation using different measurement methods

Abstract— The primary goal of this study was to find a measurement method for motion blur which is easy to carry out and gives results that can be reproduced from one lab to another. This method should be able to also take into account methods for reduction of motion blur such as backlight flashing. Two methods have been compared. The first method uses a high‐speed camera that permits us to directly picture the blurred‐edge profile. The second one exploits the mathematical analysis of the motion‐blur formation to construct the blurred‐edge profile from the temporal step response. Measurement results and method proposals are given and discussed.     

Motion‐blur characterization on liquid‐crystal displays

Abstract— In this paper, several methods to characterize motion blur on liquid‐crystal displays are reviewed. Based on the assumptions of smooth‐pursuit eye tracking and one‐frame temporal luminance integration, a simple algorithm has been proposed to calculate the normalized blurred edge width (N‐BEW) and motion‐picture response time (MPRT) with a one‐frame‐time moving‐window function to LC temporal step response curves. A custom measurement system with a fast‐eye‐sensitivity‐compensated photodiode has been developed to characterize motion blur based on LC response curves (LCRCs). MPRT values obtained by using the algorithm mentioned above and those from the smooth‐pursuit‐camera methods agree. Perception experiments were conducted to validate the correspondence between the simulated results and actual perceived images by the human eyes. In addition, the insufficiency of MPRT to evaluate motion blur on impulse‐type light‐generation LCDs, by analyzing the measurement results of a scanning backlight LCD, is discussed.     

Implicit Hierarchical Quad‐Dominant Meshes

We present a method for producing quad‐dominant subdivided meshes, which supports both adaptive refinement and adaptive coarsening. A hierarchical structure is stored implicitly in a standard half‐edge data structure, while allowing us to efficiently navigate through the different level of subdivision. Subdivided meshes contain a majority of quad elements and a moderate amount of triangles and pentagons in the regions of transition across different levels of detail. Topological LOD editing is controlled with local conforming operators, which support both mesh refinement and mesh coarsening. We show two possible applications of this method: we define an adaptive subdivision surface scheme that is topologically and geometrically consistent with the Catmull–Clark subdivision; and we present a remeshing method that produces semi‐regular adaptive meshes.     

Motion adaptive CODEC Feedforward Driving for LCD overdrive

Abstract— The authors have been developing a Feedforward Driving scheme as an overdrive technique to improve LCD response time. Focusing on the reduction of frame memory in overdrive in particular, they are now studying a memory‐reduction method by applying an image‐compression technique. An LSI has already been developed that incorporates a Compression Feedforward Driving unit, which successfully reduced image data to 1/3 by means of the image‐compression technique. This paper reports a study of Motion Adaptive CODEC Feedforward Driving in which a motion adaptation process is added to the CODEC section of the Compression Feedforward Driving unit. This motion adaptation process reduces the amount of errors in overdrive that are caused by memory reduction by using a circuit of the same scale as that for Compression Feedforward Driving.     

Forward‐adaptive method for context‐based compression of large binary images

A method for compressing large binary images is proposed for applications where spatial access to the image is required. The proposed method is a two‐stage combination of forward‐adaptive modeling and backward‐adaptive context based compression with re‐initialization of statistics. The method improves compression performance significantly in comparison to a straightforward combination of JBIG and tiling. Only minor modifications to the QM‐coder are required, and therefore existing software implementations can be easily utilized. Technical details of the modifications are provided. Copyright © 1999 John Wiley & Sons, Ltd.     

Shape‐adaptive 3‐D mesh simplification based on local optimality measurement

Mesh simplification is the process of reducing the number of triangles in a mesh representation of object surface. For a given level of detail or error tolerance, the conventional mesh simplification algorithms maximize the edge length globally, without explicitly considering local object shape. In this paper, we present a shape‐adaptive mesh simplification algorithm that locally maximizes edge length, depending on local shape. The proposed algorithm achieves shape‐adaptive simplification by iteratively maximizing edges between vertices, based on comparison with the ‘optimal’ edge lengths derived from local directional curvatures for a given error tolerance. Edge‐based processing facilitates the local shape adaptation and preserves sharp features. Experimental results demonstrate the efficacy of the proposed algorithm, by showing good visual quality and extremely small approximation error. Copyright © 2003 John Wiley & Sons, Ltd.     

Towards a goal‐driven approach to action selection in self‐adaptive software

Self‐adaptive software is a closed‐loop system, since it continuously monitors its context (i.e. environment) and/or self (i.e. software entities) in order to adapt itself properly to changes. We believe that representing adaptation goals explicitly and tracing them at run‐time are helpful in decision making for adaptation. While goal‐driven models are used in requirements engineering, they have not been utilized systematically yet for run‐time adaptation. To address this research gap, this article focuses on the deciding process in self‐adaptive software, and proposes the Goal‐Action‐Attribute Model (GAAM). An action selection mechanism, based on cooperative decision making, is also proposed that uses GAAM to select the appropriate adaptation action(s). The emphasis is on building a light‐weight and scalable run‐time model which needs less design and tuning effort comparing with a typical rule‐based approach. The GAAM and action selection mechanism are evaluated using a set of experiments on a simulated multi‐tier enterprise application, and two sample ordinal and cardinal action preference lists. The evaluation is accomplished based on a systematic design of experiment and a detailed statistical analysis in order to investigate several research questions. The findings are promising, considering the obtained results, and other impacts of the approach on engineering self‐adaptive software. Although, one case study is not enough to generalize the findings, and the proposed mechanism does not always outperform a typical rule‐based approach, less effort, scalability, and flexibility of GAAM are remarkable. Copyright © 2011 John Wiley & Sons, Ltd.     

Scale‐aware Structure‐Preserving Texture Filtering

This paper presents a novel method to enhance the performance of structure‐preserving image and texture filtering. With conventional edge‐aware filters, it is often challenging to handle images of high complexity where features of multiple scales coexist. In particular, it is not always easy to find the right balance between removing unimportant details and protecting important features when they come in multiple sizes, shapes, and contrasts. Unlike previous approaches, we address this issue from the perspective of adaptive kernel scales. Relying on patch‐based statistics, our method identifies texture from structure and also finds an optimal per‐pixel smoothing scale. We show that the proposed mechanism helps achieve enhanced image/texture filtering performance in terms of protecting the prominent geometric structures in the image, such as edges and corners, and keeping them sharp even after significant smoothing of the original signal.     

On‐off iterative adaptive controller for low‐power micro‐robotic step regulation

A novel model‐free iterative adaptive controller is presented for low‐power control of piezoelectric actuators. The controller uses simple adaptation rules based on known general behavior of piezoelectric actuators to adjust on‐off switching times to drive piezoelectric actuators through a desired transient step motion. Adaptation rules are based on small numbers of measurements taken during each iteration of the actuator movement. Combined with the use of only on‐off control inputs, controller implementation can be possible at much lower overall power levels than would be needed to implement a conventional control strategy such as through pulse‐width‐modulation (PWM) with real‐time feedback. Such power savings are particularly important for the intended controller application to piezoelectric microactuators driving autonomous terrestrial micro‐robots. A method for predicting convergence of systems with nominally linear dynamics and unknown, bounded nonlinearities is described, and applied to a sample target piezoelectric actuator. The controller is tested in simulation and experimentally on a piezoelectric cantilever actuator, and shows predicted convergence to the desired response. Copyright © 2011 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society