Motion In Image Sequences Research Articles

An investigation of a cost-effective solution for multimedia medical information management

The unstructured paper-based medical document contains heterogeneous data formats, such as text-based medical reports, graphics data, such as electrocardiograms, radiographic snapshots, such as Chest X-rays and MRI, possibly motion image sequences, such as angiograms, and verbal comments of physicians in surgeries. These multimedia information are currently stored in paper folders as print-outs, films, or tapes. The information has a high risk of being misfiled or wearing out. Advances in multimedia technology have made possible the authoring, storage and presentation of medical information in a systematic and easily-accessible way. This paper discusses the background and rationale that led to the design and prototyping of a computerized cost-effective multimedia medical document system.

特集 マルチメディア時代の画像処理 フレーム間統合による高精細ディジタル画像の獲得

When an object in a scene is moving slowly and/or the camera is being moved, the observed image sequence contains rich information about both the moving object and the scene. In this case, it seems that we can enhance spatial resolution within a region of interest in the observed image frame by integrating pixels over multiple observed image frames. The interframe-integration task involves a method for estimating interframe pixel correspondence with real pixel accuracy. The principal existing block-matching algorithm can provide highly accurate correspondence estimates only in the case in which a rigid object undergoes translation in a direction parallel to the image plane, it cannot cope with more general types of motion such as rotation. Standard gradient-based algorithms cannot stably provide accurate correspondence estimates for real moving images. In this paper, we present a method for estimating interframe pixel correspondence with real pixel accuracy. The system uses iteratively warping quadrilateral patches covering the region of interest, and is an interframe integration method. Experimental simulations conducted on real moving image sequences demonstrate that the proposed method enhances spatial resolution considerably when a region of interest is limited to one planar surface of an object.

Hierarchical variable block size motion estimation technique for motion sequence coding

Motion-compensated coding, which exploits the temporal redundancies in the moving images, is one of the most popular techniques currently used. Recently, a variable block size (VBS) motion estimation technique has been proposed to improve the performance of the motioncompensated transform coding (MCTC). This technique allows larger blocks to be used when smaller blocks provide little gain, saving the bit rates especially for areas containing more complex motion. However, there have been few efforts to investigate an efficient VBS motion structure for reducing the motion vector coding rates further. Hence, a new VBS motion estimation technique based on a hierarchical structure is proposed that improves the motion vector encoding efficiency and reduces the number of motion vectors to be transmitted as well. Specifically, the gain/cost motion estimation technique with the selective motion prediction is utilized for the topmost level motion vector search, exploiting the redundancies among the neighboring motion vectors. Also, a restricted search with respect to the topmost level motion vector enables more flexible and efficient motion vector encoding for the remaining lower level blocks. Intensive simulation on several moving image sequences show that the MCTC employing the VBS motion estimation provides a performance improvement of 0.7 to 1.0 dB, in terms of peak SNR, compared with the fixed block size motion estimation.

Book Rvw: Motion Analysis and Image Sequence Processing. Edited by M. Ibrahim Sezan and Reginald L. Lagendijk

The <i>Journal of Electronic Imaging</i> (JEI), copublished bimonthly with the Society for Imaging Science and Technology, publishes peer-reviewed papers that cover research and applications in all areas of electronic imaging science and technology.

Contour image sequence compression through motion analysis and hybrid coding method

This paper presents a motion analysis algorithm (MAA) and a hybrid coding method for contour image sequence compression. The contour image sequence consists of objects moving and rotating in a 3-D world with occlusion, shape, and size variations from frame to frame. The MAA separates the moving image sequence into several object-oriented subsequences (OOSs). In each OOS, the component is either stationary or moves smoothly, and the motion parameters can be easily estimated. The first and last frames of OOS are key frames, and the others are in-between frames. The key frames are unpredictable, and the entire frames need to be encoded. The in-between frames are compensable, and they are encoded by the motion parameter coding. The hybrid coder uses vectorgraph coding to remove spatial redundancy of the key frames and motion parameter coding to reduce the temporal redundancy of the OOSs. The motion parameters are encoded as combinations of 2-D translation, 2-D rotation, and scaling. There are many applications for contour image sequence compression. The cartoon image sequence (a sequence of line drawing sketches) and the high-frame-rate videophone for sign language transmission are good examples. Experiments show that our method encodes the contour image sequence at a very high compression ratio without losing intelligibility.

On the detection of motion and the computation of optical flow

A method for the detection of motion in image sequences is presented. In this method, the intensity history at each pixel is convolved with the second derivative in time of a temporal Gaussian smoothing function. The zero crossings in a single frame of the resulting function indicate the positions of moving edges. Intensity changes in time due to illumination effects do not produce zero crossings; thus, they are not interpreted as motion by the present method. It is also shown that the spatial and temporal derivatives of this function can be used to compute the component of the optical flow that is normal to the zero-crossing contours. This computation is also insensitive to nonconvective temporal and spatial variations in the image intensity that are caused by illumination effects.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Measurement of target motion in image sequence

In automatic image tracking systems, Ihe motion information on the target image is a very important cue for locking onto the aim point. A four points matching approach for measuring the motion information of a target image in a dynamic image sequence is proposed. Comparing with two simple spatio-temporal gradient approaches, it provides good measurements in a gaussian noisy image sequence. An algorithm for extracting four points of a target image by entropic segmentation is developed. The effect of different pre-processing techniques is also discussed. Finally, the simulations are effected by a natural FLIR target image template with two artificial manoeuvring paths. The simulation results appear satisfactory even in a noise corrupted medium.

Adaptive constrained recursive motion field and image sequence estimation

Adaptive constrained recursive motion field and image sequence estimation

Low bit-rate image sequence coding using spatial decomposition

The technique described has been developed from the still-picture version of the recursive binary nesting algorithm to code moving image sequences efficiently at low bit rates. The technique, based on quad-tree decomposition and spatial interpolation, had to be modified from its previous form so that it could make use of the additional time-axis redundancy available in a moving sequence, and also to remove a number of disturbing artifacts that were initially present. Once these topics were successfully dealt with, aspects of coding efficiency were considered by concentrating on controlling the degree of image decomposition. Details of these techniques are described in the paper, which concludes with comparisons with other coding techniques.

Image compression by Gabor expansion

A compression technique based on a pyramidal expansion is presented. The elementary functions of the expansion form a class of pyramidal Gabor functions partitioning the frequency domain into different regions. Still images and moving image sequences are coded by Selecting and quantizing the coefficients in this expansion. Computer simulation of the proposed method show good quality reconstruction of both still images and image sequences.

Use of Fourier descriptors for the estimation of general motion in image sequences

Motion estimation in image coding using block matching and pel-recursive algorithms is almost always restricted to pure translation. A new technique using Fourier descriptors (FDs), which estimates general 2-D motion, including translation, rotation, and scaling is reported.

Coding moving image sequences by segmentation of difference frames and motion-adaptive frame interpolation

Motion-compensated difference frames derived from a moving image sequence are adaptively segmented into regions of constant intensities. Region boundaries are then coded and transmitted together with region intensities. Only alternate frames are coded and transmitted, skipped frames being reproduced at the receiver by motion-adaptive interpolation. The resulting quality of the reconstructed sequence is markedly superior to that obtained when segmentation is applied to the image frames themselves.

Use of recursive binary nesting for coding moving image sequences

Recursive binary nesting (RBN) is a quadtree-based interpolation technique originally developed for still picture coding, which we have modified efficiently to code moving sequences. When the basic technique is used for motion coding, visually disturbing effects occur. The causes of these are identified and the algorithm modified to remove them.

Model of human visual-motion sensing.

We propose a model of how humans sense the velocity of moving images. The model exploits constraints provided by human psychophysics, notably that motion-sensing elements appear tuned for two-dimensional spatial frequency, and by the frequency spectrum of a moving image, namely, that its support lies in the plane in which the temporal frequency equals the dot product of the spatial frequency and the image velocity. The first stage of the model is a set of spatial-frequency-tuned, direction-selective linear sensors. The temporal frequency of the response of each sensor is shown to encode the component of the image velocity in the sensor direction. At the second stage, these components are resolved in order to measure the velocity of image motion at each of a number of spatial locations and spatial frequencies. The model has been applied to several illustrative examples, including apparent motion, coherent gratings, and natural image sequences. The model agrees qualitatively with human perception.

Interframe coding of moving image sequences

A new interframe coding technique is proposed, where a two-dimensional Hadamard transform is applied on each sub-block of successive frames, and an adaptive vector quantization scheme is applied along the transformed blocks of the successive frames. The performance of the algorithm is evaluated by computer simulation on a sequence of moving images.