Sub-pixel Motion Estimation Research Articles

Estimation of Subpixel Motion Using Bispectrum

Motion estimation techniques are widely used in today's video processing systems. The frequently used techniques are frequency-domain motion estimation methods, most notably phase correlation (PC). If the image frames are corrupted by Gaussian noises, then cross-correlation and related techniques do not work well. In this paper, however, we have studied this topic from a viewpoint different from the above. Our scheme is based on the bispectrum method for sub-pixel motion estimation of noisy image sequences. Experimental results show that our proposed method performs significantly better than PC technique.

Ordinal Regression Based Subpixel Shift Estimation for Video Super-Resolution

We present a supervised learning-based approach for subpixel motion estimation which is then used to perform video super-resolution. The novelty of this work is the formulation of the problem of subpixel motion estimation in a ranking framework. The ranking formulation is a variant of classification and regression formulation, in which the ordering present in class labels namely, the shift between patches is explicitly taken into account. Finally, we demonstrate the applicability of our approach on superresolving synthetically generated images with global subpixel shifts and enhancing real video frames by accounting for both local integer and subpixel shifts.

Reciprocal Subpixel Motion Estimation: Video Coding With Limited Hardware Resources

Conventional block-based video coding with subpixel motion compensation, requires a large pool of memory for storing up-sampled reference frames. The size of this memory for many applications, especially for encoding high definition source materials is a major design consideration. In this paper, the concept of reciprocal block matching is introduced based on the relativity of motion, especially, the translational motion. As one of the main applications for this technique, subpixel motion estimation is revisited to achieve efficient video coding when the underlying hardware only provides a small size of memory. A byproduct of the proposed algorithm is an encoding-speed boost when the encoder is to be deployed on a hardware platform with general-purpose data-caching features. This includes almost all personal computers which happen to be the main platform for desktop publishing applications. Analysis of direct (conventional) and reciprocal (proposed) subpixel motion estimation is provided to identify the sources of discrepancies between these two techniques. Finally, experimental results are provided to show the efficiency of proposed block matching scheme. All simulations are done within the frame work of reference H.264/AVC video coder

Interpolation Free Subpixel Accuracy Motion Estimation

Subpixel motion estimation plays an important role in compression efficiency within modern video codecs such as MPEG2, MPEG4, and H.264. Subpixel motion estimation is implemented within these standards using interpolated values at 1/2 or 1/4 pixel accuracy. Such interpolation gives a good reduction in residual energy for each predicted macroblock and, therefore, improves compression. However, this leads to a significant increase in computational complexity at the encoder. This is especially true for H.264 where the cost of an exhaustive set of macroblock segmentations need to be estimated in order to obtain an optimal mode for prediction. This paper presents a novel interpolation-free scheme for subpixel motion estimation using the result of the full pixel sum of absolute difference distribution of each motion compensated block applied to an H.264 encoder. This system produces reduced complexity motion estimation with a controllable tradeoff between compression performance and encoder speed. These methods facilitate the generation of a real time software H.264 encoder

Superresolution reconstruction of a video captured by a vibrated time delay and integration camera

Various applications such as industrial product inspection or low signal-to-noise situations (as in thermal imaging) employ a time delay and integration (TDI) scanning imaging technique. Due to common vibration sources such as the camera platform motion or the thermal detector's cooling system, the acquired image may be degraded by severe shift-variant geometric distortions and motion blur. We use these vibrations in terms of superresolution to create an improved high-resolution video sequence from the degraded lower resolution sequence, in two main stages: subpixel motion estimation with respect to translations and rotations, used for point spread function (PSF) estimation, followed by an efficient implementation of the projection onto convex sets (POCS) method. We generalize and considerably improve a previous technique for restoration of a single image captured by a translational vibrated staggered-TDI camera (Hochman et al., 2004). The proposed method is implemented with both simulated videos and real degraded thermal videos. A comparative analysis shows an advantage of the proposed method over others in restoring the vibrated videos.

A markerless sub-pixel motion estimation technique to reconstruct kinematics and estimate the centre of mass in posturography

A novel method to evaluate postural sway is presented: balance strategies are identified by applying a markerless image processing algorithm to video sequences obtained from commercially available systems. The motion estimation technique for the analysis of video sequences is a coarse to fine procedure based on the block matching algorithm (BMA). The method makes it possible to estimate the movement of selected elements on the scene with a sub-pixel precision. It has been done by applying a bicubic spline interpolation to the coarse results obtained by the BMA. Results achieved through the analysis of synthetic video tests make it possible to determine the accuracy of the proposed sub-pixel algorithm. Figures show how the proposed method can be confidently applied to evaluate postural sway. The proposed method has been applied to videos recorded during orthostatic posture trials in different conditions, and to combined tests where signals from a balance plate have been acquired simultaneously to the video sequence. The results show the usefulness of the proposed approach in order to evaluate balance strategies in posturography.

Performance study of gradient correlation for sub-pixel motion estimation in the frequency domain

The authors present a performance study of gradient correlation in the context of the estimation of interframe motion in video sequences. The method is based on the maximisation of the spatial gradient cross-correlation function, which is computed in the frequency domain and therefore can be implemented by fast transformation algorithms. Enhancements to the baseline gradient-correlation algorithm are presented which further improve performance, especially in the presence of noise. A comparative performance study is also presented, which demonstrates that the proposed method outperforms state-of-the-art methods in frequency-domain motion estimation, in the shape of phase correlation, in terms of sub-pixel accuracy for a range of test material and motion scenarios.

Fast sub-pixel motion estimation techniques having lower computational complexity

This paper proposes fast sub-pixel motion estimation techniques having lower computational complexity. The proposed methods are based on mathematical models of the motion-compensated prediction errors in compressing moving pictures. Unlike conventional hierarchical motion estimation techniques, the proposed methods avoid sub-pixel interpolation and subsequent secondary search after the integer-precision motion estimation, resulting in reduced computational time. In order to decide the coefficients of the models, the motion-compensated prediction errors of the neighboring pixels around the integer-pixel motion vector are utilized. The prediction errors, here, were already obtained during the pixel accuracy motion search. Once the coefficients are determined, the models estimate motion compensated prediction errors at sub-pixel locations surrounding the integer-pixel motion vector, yielding the sub-pixel motion vector. The performance of the proposed methods, despite substantially lower computational complexity, is close to that of the conventional interpolation-and-search method.

PPHPS: a parabolic prediction-based, fast half-pixel search algorithm for very low bit-rate moving-picture coding

In hybrid moving-picture coding schemes, motion estimation is conducted in two stages, one at integer pixel accuracy and the other at subpixel accuracy. In very low bit-rate coding, some fast motion-search algorithms are able to decrease their search points to about ten pixels at the integer pixel search stage. There remains, however, a need to study fast computing for the subpixel motion estimation. A novel, fast-search algorithm using parabolic prediction is proposed in this paper particularly for the half-pixel motion vector estimation. It needs to check only three half-pixels rather than the eight pixels, which are used in the full half-pixel motion search scheme (FHPS). Experimental results show that this algorithm preserves the image quality and has little influence on the bit-rate when compared to that of the referenced FHPS strategy.

Estimation of sub-pixel motion using gradient cross-correlation

A computationally efficient scheme suitable for the estimation of sub-pixel motion in video sequences is presented. The scheme is based on the maximisation of the cross-correlation function between spatial gradient information derived from a pair of images. The proposed scheme is highly accurate, outperforms established frequency-domain motion estimation methods and is considerably more immune to noise.

Interpolation-free subpixel motion estimation techniques in DCT domain

Currently existing subpixel motion estimation algorithms require interpolation of interpixel values which undesirably increases the overall complexity and data flow and deteriorates the estimation accuracy. We develop discrete cosine transform (DCT)-based techniques to estimate subpel motion at different desired subpel levels of accuracy in the DCT domain without interpolation. We show that subpixel motion information is preserved in the DCT of a shifted signal under some condition in the form of pseudophases, and we establish subpel sinusoidal orthogonal principles to extract this information. The proposed subpixel techniques are flexible and scalable in terms of estimation accuracy with very low computational complexity O(N/sup 2/) compared to O(N/sup 4/) for the full-search block-matching approach and its subpixel versions. Above all, motion estimation in the DCT domain instead of the spatial domain simplifies the conventional hybrid DCT-based video coder, especially the heavily loaded feedback loop in the conventional design, resulting in a fully DCT-based high-throughput video codec. In addition, the computation of pseudophases is local, and thus a highly parallel architecture is feasible for the DCT-based algorithms. Finally, simulation on video sequences of different characteristics shows comparable performance of the proposed algorithms to block-matching approaches.

Subpixel Motion Estimation for Super-Resolution Image Sequence Enhancement

Super-resolution enhancement algorithms are used to estimate a high-resolution video still (HRVS) from several low-resolution frames, provided that objects within the digital image sequence move with subpixel increments. A Bayesian multi_frame enhancement algorithm is presented to compute an HRVS using the spatial information present within each frame as well as the temporal information present due to object motion between frames. However, the required subpixel-resolution motion vectors must be estimated from low-resolution and noisy video frames, resulting in an inaccurate motion field which can adversely impact the quality of the enhanced image. Several subpixel motion estimation techniques are incorporated into the Bayesian multiframe enhancement algorithm to determine their efficacy in the presence of global data transformations between frames (i.e., camera pan, rotation, tilt, and zoom) and independent object motion. Visual and quantitative comparisons of the resulting high-resolution video stills computed from two video frames and the corresponding estimated motion fields show that the eight-parameter projective motion model is appropriate for global scene changes, while block matching and Horn–Schunck optical flow estimation each have their own advantages and disadvantages when used to estimate independent object motion.

Sub-pixel motion estimation with 3-D recursive search block-matching

Recently the 3-D Recursive Search Block-Matching algorithm was introduced as a high quality, low-cost, true-motion estimation method suitable for critical field rate conversion applications. In this article an extension of the algorithm is presented that provides a sub-pixel accuracy of the estimated motion vectors. This significantly broadens the applicability of the algorithm in the area of interlaced-to-sequential scan conversion and coding. The extension is such that it hardly adds any calculational complexity, which implies that the attractiveness of the algorithm for a VLSI implementation remains high. Even more, a simplified version of the algorithm, the Y-prediction block-matcher, is suggested that offers sub-pixel accuracy, a large range of motion vectors, and an extremely low complexity requiring only four candidate vectors per block. An evaluation of this estimator is included in the paper.

Sub-pixel motion estimation with 3-D recursive search block-matching

Abstract Recently the 3-D Recursive Search Block-Matching algorithm was introduced as a high quality, low-cost, true-motion estimation method suitable for critical field rate conversion applications. In thisarticle an extension of the algorithm is presented that provides a sub-pixel accuracy of the estimated motion vectors. This significantly broadens the applicability of the algorithm in the area of interlaced-to-sequential scan conversion and coding. The extension is such that it hardly adds any calculational complexity, which implies that the attractiveness of the algorithm for a VLSI implementation remains high. Even more, a simplified version of the algorithm, the Y-prediction block-matcher, is suggested that offers sub-pixel accuracy, a large range of motion vectors, and an extremely low complexity requiring only four candidate vectors per block. An evaluation of this estimator is included in the paper.