Sub-pixel Motion Research Articles

An efficient statistical method for subpixel optical flow detection

In this paper, we show that the randomized sampling and voting process detects optical flow. We introduce a random sampling method for solving the least-squares model-fitting problem using a mathematical property for the construction of pseudo-inverse. Using an appropriate number of images from a sequence of images, our method detects subpixel motion in this sequence. It is possible to compute subpixel motions from a long-time interval. We use the accumulator space for the unification of these flow vectors which are computed from different time intervals. Numerical examples for the test image sequences show the performance of our method.

Discrete cosine transform based high-resolution image reconstruction considering the inaccurate subpixel motion information

The demand for high-resolution images is gradually increasing, whereas many imaging systems have been designed to enable a certain level of aliasing during image acquisition. in this sense, digital image processing approaches have recently been investigated to reconstruct a high-resolution image from aliased low-resolution images. However, since the subpixel motion information is assumed to be accurate in most conventional approaches, the satisfactory high-resolution image cannot be obtained when the subpixel motion information is inaccurate. Hence, we propose a new algorithm to reduce the distortion in the reconstructed high-resolution image due to the inaccuracy of subpixel motion information. For this purpose, we analyze the effect of inaccurate subpixel motion information on a high-resolution image reconstruction, and model it as zero-mean additive Gaussian errors added respectively to each low-resolution image. To reduce the distortion, we apply the modified multichannel image deconvolution approach to the problem. The validity of the proposed algorithm is demonstrated both theoretically and experimentally.

Block-matching algorithm for mitigating aliasing effects in undersampled image sequences

Two fundamental motivations exist for designing remote sensing systems that are undersampled: (1) SNR considerations that motivate larger detectors to collect more photoevents per frame time and (2) the desire to maximize the field of view with a finite number of detectors. As a result, many remote sensing systems do not satisfy the Nyquist sampling criterion, leading to measured images corrupted with a defect called aliasing. We describe a localized subpixel motion sensing algorithm that is used to properly place small blocks of the sequence of images in an upsampled space. Localized motion sensing enables dealiasing to be performed on image sequences with more complicated relative motion than simple translation. The presented results show improvements in both the edge response and subjective image quality.

Motion Compensation on DCT Domain

Alternative fully DCT-based video codec architectures have been proposed in the past to address the shortcomings of the conventional hybrid motion compensated DCT video codec structures traditionally chosen as the basis of implementation of standard-compliant codecs. However, no prior effort has been made to ensure interoperability of these two drastically different architectures so that fully DCT-based video codecs are fully compatible with the existing video coding standards. In this paper, we establish the criteria for matching conventional codecs with fully DCT-based codecs. We find that the key to this interoperability lies in the heart of the implementation of motion compensation modules performed in the spatial and transform domains at both the encoder and the decoder. Specifically, if the spatial-domain motion compensation is compatible with the transform-domain motion compensation, then the states in both the coder and the decoder will keep track of each other even after a long series of P-frames. Otherwise, the states will diverge in proportion to the number of P-frames between two I-frames. This sets an important criterion for the development of any DCT-based motion compensation schemes. We also discuss and develop some DCT-based motion compensation schemes as important building blocks of fully DCT-based codecs. For the case of subpixel motion compensation, DCT-based approaches allow more accurate interpolation without any increase in computation. Furthermore, a scare number of DCT coefficients after quantization significantly decreases the number of calculations required for motion compensation. Coupled with the DCT-based motion estimation algorithms, it is possible to realize fully DCT-based codecs to overcome the disadvantages of conventional hybrid codecs.

An illumination invariant algorithm for subpixel accuracy image stabilization and its effect on MPEG-2 video compression

This paper offers a fast and simple near-closed-form solution for the least mean-squared-error (LMSE) estimation of the frame-to-frame global subpixel motion in an unsteady image sequence. The offered near-closed-form solution achieves unlimited subpixel accuracy by always employing a small and fixed number of computations, independent of the desired subpixel accuracy. The algorithm is designed so that it is insensitive to frame-to-frame intensity variations, which is a distinctive feature of the method. Experimental results demonstrate the superiority of the proposed method to the spatio-temporal differentiation and surface fitting algorithms under different illumination conditions. This paper furthermore discusses the effect of the proposed image stabilization algorithm on the performance of MPEG-2 video compression. We report that removal of global motion down to subpixel accuracy from an unsteady video improves MPEG-2 compression performance significantly (by at least 1 dB for all frame types), in spite of the fact that motion vectors are differentially encoded in MPEG-2. This result is supported via experimental results using the proposed subpixel registration algorithm and an analysis of the macroblock coding preferences accepted in MPEG-2.

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.

An improved method for MRI artifact correction due to translational motion in the imaging plane

A computer postprocessing technique is developed to remove MRI artifact arising from unknown translational motion in the imaging plane. Based on previous artifact correction methods, the improved technique uses two successive steps to reduce read out and phase-encoding direction artifacts: First, the spectrum shift method is applied to remove read-out axis translational motion. Then, the phase retrieval method is employed to eliminate the remaining subpixel motion of the read-out axis and the entire motion of the phase-encoding axis. In the presence of noise, to protect edge detection (in the spectrum shift method), two high-density gray-level markers are added, one to each side of the imaging object. Experimental results with an actual MR scan confirmed the ability of the method to correct the artifact of an MR image caused by unknown translational motion in the imaging plane.

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.