Showing papers on "Image processing published in 1995"

Spatial registration and normalization of images

Abstract: This paper concerns the spatial and intensity transformations that map one image onto another. We present a general technique that facilitates nonlinear spatial (stereotactic) normalization and image realignment. This technique minimizes the sum of squares between two images following nonlinear spatial deformations and transformations of the voxel (intensity) values. The spatial and intensity transformations are obtained simultaneously, and explicitly, using a least squares solution and a series of linearising devices. The approach is completely noninteractive (automatic), nonlinear, and noniterative. It can be applied in any number of dimensions. Various applications are considered, including the realignment of functional magnetic resonance imaging (MRI) time-series, the linear (affine) and nonlinear spatial normalization of positron emission tomography (PET) and structural MRI images, the coregistration of PET to structural MRI, and, implicitly, the conjoining of PET and MRI to obtain high resolution functional images. © 1995 Wiley-Liss, Inc.

Optical image encryption based on input plane and Fourier plane random encoding.

Abstract: We propose a new optical encoding method of images for security applications. The encoded image is obtained by random-phase encoding in both the input and the Fourier planes. We analyze the statistical properties of this technique and show that the encoding converts the input signal to stationary white noise and that the reconstruction method is robust.

Correction for geometric distortion in echo planar images from B0 field variations

Abstract: A method is described for the correction of geometric distortions occurring in echo planar images. The geometric distortions are caused in large part by static magnetic field inhomogeneities, leading to pixel shifts, particularly in the phase encode direction. By characterizing the field inhomogeneities from a field map, the image can be unwarped so that accurate alignment to conventionally collected images can be made. The algorithm to perform the unwarping is described, and results from echo planar images collected at 1.5 and 4 Tesla are shown.

Markov Random Field Modeling in Computer Vision

Abstract: From the Publisher: Markov random field (MRF) theory provides a basis for modeling contextual constraints in visual processing and interpretation. It enables us to develop optimal vision algorithms systematically when used with optimization principles. This book presents a comprehensive study on the use of MRFs for solving computer vision problems. The book covers the following parts essential to the subject: introduction to fundamental theories, formulations of MRF vision models, MRF parameter estimation, and optimization algorithms. Various vision models are presented in a unified framework, including image restoration and reconstruction, edge and region segmentation, texture, stereo and motion, object matching and recognition, and pose estimation. This book is an excellent reference for researchers working in computer vision, image processing, statistical pattern recognition, and applications of MRFs. It is also suitable as a text for advanced courses in these areas.

The computation of optical flow

Abstract: Two-dimensional image motion is the projection of the three-dimensional motion of objects, relative to a visual sensor, onto its image plane. Sequences of time-orderedimages allow the estimation of projected two-dimensional image motion as either instantaneous image velocities or discrete image displacements. These are usually called the optical flow field or the image velocity field. Provided that optical flow is a reliable approximation to two-dimensional image motion, it may then be used to recover the three-dimensional motion of the visual sensor (to within a scale factor) and the three-dimensional surface structure (shape or relative depth) through assumptions concerning the structure of the optical flow field, the three-dimensional environment, and the motion of the sensor. Optical flow may also be used to perform motion detection, object segmentation, time-to-collision and focus of expansion calculations, motion compensated encoding, and stereo disparity measurement. We investigate the computation of optical flow in this survey: widely known methods for estimating optical flow are classified and examined by scrutinizing the hypothesis and assumptions they use. The survey concludes with a discussion of current research issues.

Model-based object pose in 25 lines of code

Abstract: In this paper, we describe a method for finding the pose of an object from a single image. We assume that we can detect and match in the image four or more noncoplanar feature points of the object, and that we know their relative geometry on the object. The method combines two algorithms; the first algorithm,POS (Pose from Orthography and Scaling) approximates the perspective projection with a scaled orthographic projection and finds the rotation matrix and the translation vector of the object by solving a linear system; the second algorithm,POSIT (POS with ITerations), uses in its iteration loop the approximate pose found by POS in order to compute better scaled orthographic projections of the feature points, then applies POS to these projections instead of the original image projections. POSIT converges to accurate pose measurements in a few iterations. POSIT can be used with many feature points at once for added insensitivity to measurement errors and image noise. Compared to classic approaches making use of Newton's method, POSIT does not require starting from an initial guess, and computes the pose using an order of magnitude fewer floating point operations; it may therefore be a useful alternative for real-time operation. When speed is not an issue, POSIT can be written in 25 lines or less in Mathematica; the code is provided in an Appendix.

Alignment by maximization of mutual information

Abstract: A new information-theoretic approach is presented for finding the pose of an object in an image. The technique does not require information about the surface properties of the object, besides its shape, and is robust with respect to variations of illumination. In our derivation, few assumptions are made about the nature of the imaging process. As a result, the algorithms are quite general and can foreseeably be used in a wide variety of imaging situations. Experiments are presented that demonstrate the approach in registering magnetic resonance images, aligning a complex 3D object model to real scenes including clutter and occlusion, tracking a human head in a video sequence and aligning a view-based 2D object model to real images. The method is based on a formulation of the mutual information between the model and the image. As applied in this paper, the technique is intensity-based, rather than feature-based. It works well in domains where edge or gradient-magnitude based methods have difficulty, yet it is more robust then traditional correlation. Additionally, it has an efficient implementation that is based on stochastic approximation. >

Nonlinear image recovery with half-quadratic regularization

Abstract: One popular method for the recovery of an ideal intensity image from corrupted or indirect measurements is regularization: minimize an objective function that enforces a roughness penalty in addition to coherence with the data. Linear estimates are relatively easy to compute but generally introduce systematic errors; for example, they are incapable of recovering discontinuities and other important image attributes. In contrast, nonlinear estimates are more accurate but are often far less accessible. This is particularly true when the objective function is nonconvex, and the distribution of each data component depends on many image components through a linear operator with broad support. Our approach is based on an auxiliary array and an extended objective function in which the original variables appear quadratically and the auxiliary variables are decoupled. Minimizing over the auxiliary array alone yields the original function so that the original image estimate can be obtained by joint minimization. This can be done efficiently by Monte Carlo methods, for example by FFT-based annealing using a Markov chain that alternates between (global) transitions from one array to the other. Experiments are reported in optical astronomy, with space telescope data, and computed tomography. >

Rapid scene analysis on compressed video

Abstract: Several rapid scene analysis algorithms for detecting scene changes and flashlight scenes directly on compressed video are proposed. These algorithms operate on the DC sequence which can be readily extracted from video compressed using Motion JPEG or MPEG without full-frame decompression. The DC images occupy only a small fraction of the original data size while retaining most of the essential "global" information. Operating on these images offers a significant computation saving. Experimental results show that the proposed algorithms are fast and effective in detecting abrupt scene changes, gradual transitions including fade-ins and fade-outs, flashlight scenes and in deriving intrashot variations.

Motion signal processing

Abstract: Techniques from the image and signal processing domain can be successfully applied to designing, modifying, and adapting animated motion. For this purpose, we introduce multiresolution motion filtering, multitarget motion interpolation with dynamic timewarping, waveshaping and motion displacement mapping. The techniques are well-suited for reuse and adaptation of existing motion data such as joint angles, joint coordinates or higher level motion parameters of articulated figures with many degrees of freedom. Existing motions can be modified and combined interactively and at a higher level of abstraction than conventional systems support. This general approach is thus complementary to keyframing, motion capture, and procedural animation.

Wavelets for computer graphics: a primer.1

Abstract: Wavelets are a mathematical tool for hierarchically decomposing functions. They allow a function to be described in terms of a coarse overall shape, plus details that range from broad to narrow. Regardless of whether the function of interest is an image, a curve, or a surface, wavelets offer an elegant technique for representing the levels of detail present. The article is intended to provide people working in computer graphics with some intuition for what wavelets are, as well as to present the mathematical foundations necessary for studying and using them. We discuss the simple case of Haar wavelets in one and two dimensions, and show how they can be used for image compression. >

The image processing handbook (2nd ed.)

Abstract: A device for injecting medicament without the use of a needle is disclosed wherein medicament is expelled from the device at high pressure, caused to break the skin of a patient, and appropriately forced into the patient's body. A preferred embodiment of the present invention is a jet injector having a piston slidably movable within a medicament chamber to selectively change the volume of the medicament chamber and a mechanism for advancing the piston including releasably held springs which may be compressed by a winding mechanism or pressurized fluid. Medicament is provided to the medicament chamber from a medicament container mounted on the injector by a container holder assembly including flexible fingers that can be caused to grasp the pierceable cap of the medicament container. Medicament is then selectively directed from the medicament container to the medicament chamber by valving which, in a first position, interacts with a safety to provide air to the medicament container during the filling of the medicament chamber and, in a second position, allows injection into the patient while the safety prevents movement of the valve member from the second position during injection and simultaneously blocks air communication to the medicament container.

Goal-directed evaluation of binarization methods

Abstract: This paper presents a methodology for evaluation of low-level image analysis methods, using binarization (two-level thresholding) as an example. Binarization of scanned gray scale images is the first step in most document image analysis systems. Selection of an appropriate binarization method for an input image domain is a difficult problem. Typically, a human expert evaluates the binarized images according to his/her visual criteria. However, to conduct an objective evaluation, one needs to investigate how well the subsequent image analysis steps will perform on the binarized image. We call this approach goal-directed evaluation, and it can be used to evaluate other low-level image processing methods as well. Our evaluation of binarization methods is in the context of digit recognition, so we define the performance of the character recognition module as the objective measure. Eleven different locally adaptive binarization methods were evaluated, and Niblack's method gave the best performance.

Pyramid-based texture analysis/synthesis

Abstract: This paper describes a method for synthesizing images that match the texture appearance of a given digitized sample This synthesis is completely automatic and requires only the "target" texture as input It allows generation of as much texture as desired so that any object can be covered The approach is based on a model of human texture perception, and has potential to be a practically useful tool for image processing and graphics applications

The image processing handbook

Abstract: "This guide clearly explains the acquisition and use of digital images in a wide variety of scientific fields. This sixth edition features new sections on selecting a camera with resolution appropriate for use on light microscopes, on the ability of current cameras to capture raw images with high dynamic range, and on imaging in more than two dimensions. It discusses Dmax for X-ray images and combining images with different exposure settings to further extend the dynamic range. This edition also includes a new chapter on shape measurements, a review of new developments in image file searching, and a wide range of new examples and diagrams"

Texture segmentation using fractal dimension

Abstract: This paper deals with the problem of recognizing and segmenting textures in images. For this purpose the authors employ a technique based on the fractal dimension (FD) and the multi-fractal concept. Six FD features are based on the original image, the above average/high gray level image, the below average/low gray level image, the horizontally smoothed image, the vertically smoothed image, and the multi-fractal dimension of order two. A modified box-counting approach is proposed to estimate the FD, in combination with feature smoothing in order to reduce spurious regions. To segment a scene into the desired number of classes, an unsupervised K-means like clustering approach is used. Mosaics of various natural textures from the Brodatz album as well as microphotographs of thin sections of natural rocks are considered, and the segmentation results to show the efficiency of the technique. Supervised techniques such as minimum-distance and k-nearest neighbor classification are also considered. The results are compared with other techniques. >

A perceptually tuned subband image coder based on the measure of just-noticeable-distortion profile

Abstract: To represent an image of high perceptual quality with the lowest possible bit rate, an effective image compression algorithm should not only remove the redundancy due to statistical correlation but also the perceptually insignificant components from image signals. In this paper, a perceptually tuned subband image coding scheme is presented, where a just-noticeable distortion (JND) or minimally noticeable distortion (MND) profile is employed to quantify the perceptual redundancy. The JND profile provides each signal being coded with a visibility threshold of distortion, below which reconstruction errors are rendered imperceptible. Based on a perceptual model that incorporates the threshold sensitivities due to background luminance and texture masking effect, the JND profile is estimated from analyzing local properties of image signals. According to the sensitivity of human visual perception to spatial frequencies, the full-band JND/MND profile is decomposed into component JND/MND profiles of different frequency subbands. With these component profiles, perceptually insignificant signals in each subband can be screened out, and significant signals can be properly encoded to meet the visibility threshold. A new quantitative fidelity measure, termed as peak signal-to-perceptible-noise ratio (PSPNR), is proposed to assess the quality of the compressed image by taking the perceptible part of the distortion into account. Simulation results show that near-transparent image coding can be achieved at less than 0.4 b/pixel. As compared to the ISO-JPEG standard, the proposed algorithm can remove more perceptual redundancy from the original image, and the visual quality of the reconstructed image is much more acceptable at low bit rates.

A contour-based approach to multisensor image registration

Abstract: Image registration is concerned with the establishment of correspondence between images of the same scene. One challenging problem in this area is the registration of multispectral/multisensor images. In general, such images have different gray level characteristics, and simple techniques such as those based on area correlations cannot be applied directly. On the other hand, contours representing region boundaries are preserved in most cases. The authors present two contour-based methods which use region boundaries and other strong edges as matching primitives. The first contour matching algorithm is based on the chain-code correlation and other shape similarity criteria such as invariant moments. Closed contours and the salient segments along the open contours are matched separately. This method works well for image pairs in which the contour information is well preserved, such as the optical images from Landsat and Spot satellites. For the registration of the optical images with synthetic aperture radar (SAR) images, the authors propose an elastic contour matching scheme based on the active contour model. Using the contours from the optical image as the initial condition, accurate contour locations in the SAR image are obtained by applying the active contour model. Both contour matching methods are automatic and computationally quite efficient. Experimental results with various kinds of image data have verified the robustness of the algorithms, which have outperformed manual registration in terms of root mean square error at the control points. >

Digital camera with apparatus for authentication of images produced from an image file

Abstract: A digital camera equipped with a processor for authentication of images produced from an image file taken by the digital camera is provided. The digital camera processor has embedded therein a private key unique to it, and the camera housing has a public key that is so uniquely related to the private key that digital data encrypted with the private key may be decrypted using the public key. The digital camera processor comprises means for calculating a hash of the image file using a predetermined algorithm, and second means for encrypting the image hash with the private key, thereby producing a digital signature. The image file and the digital signature are stored in suitable recording means so they will be available together. Apparatus for authenticating the image file as being free of any alteration uses the public key for decrypting the digital signature, thereby deriving a secure image hash identical to the image hash produced by the digital camera and used to produce the digital signature. The authenticating apparatus calculates from the image file an image hash using the same algorithm as before. By comparing this last image hash with the secure image hash, authenticity of the image file is determined if they match. Other techniques to address time-honored methods of deception, such as attaching false captions or inducing forced perspectives, are included.

Registering multiview range data to create 3D computer objects

Abstract: Concerns the problem of range image registration for the purpose of building surface models of 3D objects. The registration task involves finding the translation and rotation parameters which properly align overlapping views of the object so as to reconstruct from these partial surfaces, an integrated surface representation of the object. The registration task is expressed as an optimization problem. We define a function which measures the quality of the alignment between the partial surfaces contained in two range images as produced by a set of motion parameters. This function computes a sum of Euclidean distances from control points on one surfaces to corresponding points on the other. The strength of this approach is in the method used to determine point correspondences. It reverses the rangefinder calibration process, resulting in equations which can be used to directly compute the location of a point in a range image corresponding to an arbitrary point in 3D space. A stochastic optimization technique, very fast simulated reannealing (VFSR), is used to minimize the cost function. Dual-view registration experiments yielded excellent results in very reasonable time. A multiview registration experiment took a long time. A complete surface model was then constructed from the integration of multiple partial views. The effectiveness with which registration of range images can be accomplished makes this method attractive for many practical applications where surface models of 3D objects must be constructed. >

Subpixel edge localization and the interpolation of still images

Abstract: In this paper, we present a nonlinear interpolation scheme for still image resolution enhancement. The algorithm is based on a source model emphasizing the visual integrity of detected edges and incorporates a novel edge fitting operator that has been developed for this application. A small neighborhood about each pixel in the low-resolution image is first mapped to a best-fit continuous space step edge. The bilevel approximation serves as a local template on which the higher resolution sampling grid can then be superimposed (where disputed values in regions of local window overlap are averaged to smooth errors). The result is an image of increased resolution with noticeably sharper edges and, in all tried cases, lower mean-squared reconstruction error than that produced by linear techniques. >

Motion estimation techniques for digital TV: a review and a new contribution

Abstract: The key to high performance in image sequence coding lies in an efficient reduction of the temporal redundancies. For this purpose, motion estimation and compensation techniques have been successfully applied. This paper studies motion estimation algorithms in the context of first generation coding techniques commonly used in digital TV. In this framework, estimating the motion in the scene is not an intrinsic goal. Motion estimation should indeed provide good temporal prediction and simultaneously require low overhead information. More specifically the aim is to minimize globally the bandwidth corresponding to both the prediction error information and the motion parameters. This paper first clarifies the notion of motion, reviews classical motion estimation techniques, and outlines new perspectives. Block matching techniques are shown to be the most appropriate in the framework of first generation coding. To overcome the drawbacks characteristic of most block matching techniques, this paper proposes a new locally adaptive multigrid block matching motion estimation technique. This algorithm has been designed taking into account the above aims. It leads to a robust motion field estimation precise prediction along moving edges and a decreased amount of side information in uniform areas. Furthermore, the algorithm controls the accuracy of the motion estimation procedure in order to optimally balance the amount of information corresponding to the prediction error and to the motion parameters. Experimental results show that the technique results in greatly enhanced visual quality and significant saving in terms of bit rate when compared to classical block matching techniques. >

Manipulation and compositing of MC-DCT compressed video

Abstract: Many advanced video applications require manipulations of compressed video signals. Popular video manipulation functions include overlap (opaque or semitransparent), translation, scaling, linear filtering, rotation, and pixel multiplication. We propose algorithms to manipulate compressed video in the compressed domain. Specifically, we focus on compression algorithms using the discrete cosine transform (DCT) with or without motion compensation (MC). Such compression systems include JPEG, motion JPEG, MPEG, and H.261. We derive a complete set of algorithms for all aforementioned manipulation functions in the transform domain, in which video signals are represented by quantized transform coefficients. Due to a much lower data rate and the elimination of decompression/compression conversion, the transform-domain approach has great potential in reducing the computational complexity. The actual computational speedup depends on the specific manipulation functions and the compression characteristics of the input video, such as the compression rate and the nonzero motion vector percentage. The proposed techniques can be applied to general orthogonal transforms, such as the discrete trigonometric transform. For compression systems incorporating MC (such as MPEG), we propose a new decoding algorithm to reconstruct the video in the transform domain and then perform the desired manipulations in the transform domain. The same technique can be applied to efficient video transcoding (e.g., from MPEG to JPEG) with minimal decoding. >

Magnetic resonance image—directed stereotactic neurosurgery: use of image fusion with computerized tomography to enhance spatial accuracy

Abstract: Distortions of the magnetic field, such as those caused by susceptibility artifacts and peripheral magnetic field warping, can limit geometric precision in the use of magnetic resonance (MR) imaging in stereotactic procedures. The authors have routinely found systematic error in MR stereotactic coordinates with a median of 4 mm compared to computerized tomography (CT) coordinates. This error may place critical neural structures in jeopardy in sme procedures. A description is given of an image fusion technique that uses a chamfer matching algorithm; the advantages of MR imaging in anatomical definition are combined with the geometric precision of CT, while eliminating most of the anatomical spatial distortion of stereotactic MR imaging. A stereotactic radiosurgical case is presented in which the use of MR localization alone would have led to both irradiation of vital neural structures outside the desired target volume and underdose of the intended target volume. The image fusion approach allows for the use of MR imaging, combined with stereotactic CT, as a reliable localizing technique for stereotactic neurosurgery and radiosurgery.

Electronic still camera for capturing and categorizing images

Abstract: An electronic camera captures images representing a variety of subjects and categorizes the image according to subject matter. The camera comprises an image sensor for capturing an image, a converter stage for converting the image into digital image data, and a memory for storing a plurality of categories providing classification of the images by subject. A processor in the camera has the capability of assigning the plurality of categories to the images captured by the camera, with each category providing a subject classification for the images. A user selects one or more categories for a plurality of images prior to capture, and an output image signal is then generated including the digital image data corresponding to a captured image and the particular category selected by the user. The categories can be default identifiers stored in the memory, or can be names, text (i.e., account number), and/or graphics overlays (i.e., company logo) entered via a host computer and uploaded to the camera memory before the pictures are taken.

Imaging device and method

Abstract: This invention is a method and apparatus (2) for obtaining and displaying in real time an image of an object (10) obtained by one modality such that the image corresponds to a line of view established by another modality. The method comprises steps of obtaining a follow image library (14) of the object via a first imaging modality; providing a lead image library (12) obtained via the second imaging modality; referencing the lead image libray to the follow image library; obtaining a lead image of the object in real time via the second imaging modality along a lead view; comparing the real time lead image to lead images in the lead image library via digital image analysis to identify a follow image line of view corresponding to the real time lead view; transforming the identified follow image to correspond to the scale, rotation, and position of the lead image; and displaying the transformed follow image.