Showing papers on "Image gradient published in 1983"

The Laplacian Pyramid as a Compact Image Code

Abstract: We describe a technique for image encoding in which local operators of many scales but identical shape serve as the basis functions. The representation differs from established techniques in that the code elements are localized in spatial frequency as well as in space. Pixel-to-pixel correlations are first removed by subtracting a lowpass filtered copy of the image from the image itself. The result is a net data compression since the difference, or error, image has low variance and entropy, and the low-pass filtered image may represented at reduced sample density. Further data compression is achieved by quantizing the difference image. These steps are then repeated to compress the low-pass image. Iteration of the process at appropriately expanded scales generates a pyramid data structure. The encoding process is equivalent to sampling the image with Laplacian operators of many scales. Thus, the code tends to enhance salient image features. A further advantage of the present code is that it is well suited for many image analysis tasks as well as for image compression. Fast algorithms are described for coding and decoding.

The Differential Method for Image Motion Estimation

Abstract: Small variations of the apparent velocity of objects imaged by television cameras can be efficiently measured comparing the frame differences with the spatial variations of the luminance. The main lobe of the autocovariance of a block of picture elements of an image is first modeled as a paraboloid; afterwards, the comparison with the mutual covariance between two successive video frames, allows to determine their relative displacement. The curvatures of the autocovariance taken at the origin are proportional to the m.s. slopes of the image along the coordinate axes; it can be shown that the slopes should be calculated using a centered differentiation, rather than a non centered one, to avoid bias in the estimation of the displacement. To be able to precisely measure the displacement along a given direction, it is necessary that the m.s. slope in that direction be high enough; in fact, the measure of temporal and spatial image derivatives only constrains the projection of the actual displacement along the image gradient. More complex, but continuous, motion fields can be estimated with simple extensions of the original formulation of the differential method. A stochastic model for the motion field is therefore introduced, in order to derive a recursive estimation technique. The component of the motion paralel to the local image gradient is updated, on a pel by pel basis, while the other one is approximately kept constant. The practical results are sufficient for image coding, but not good enough to get a nicely smooth velocity field in real situations.

Image comparison system

Abstract: Image comparison is accomplished by forming a composite image composed of a reference image and a test image. A two-dimensional image spectrum is generated from the composite image and then is whitened by setting the magnitude of every point of the two-dimensional image spectrum to a uniform level. A phase-only image of the composite image is then constructed, and values of the phase-only image exceeding a predetermined threshold are detected as an indication of the location of a difference between the reference and test images.

Image processing method based on processing of interrelated image gradients

Abstract: An improved image processing method prevents unwanted processing artifacts from degrading the reproduction of an image by stressing the interrelationship of various image gradients in the image. Image signals are generated representative of the light value of elements of the image. A local gradient signal is generated in response to a combination of image signals representative of an image gradient over a local portion of the image. An extended gradient signal is also generated representative of an image gradient over an image portion greater than the local portion. The image gradients are interrelated in a composite signal generated from a combination of the local and extended gradient signals. As an example of the combination, the composite signal is made to vary as a function of the difference between the gradient signals. The image signals are then modified subject to a characteristic of the composite signal, e.g., the magnitude of the composite signal.

Method and apparatus for reproducing an image which has a coarser resolution than utilized in scanning of the image

Abstract: Method and apparatus for the reproduction of an image with coarser resolution than used during scanning wherein the original image is opto-electronically scanned point-wise and line-wise with a prescribed resolution and is converted into digital image signals, and a field containing as many image points as is used for one coarse image point is extracted from the digital image signals, and wherein weighting is undertaken for the individual image signals of the image points of said field and a corresponding image signal for the coarse image point is obtained by means of combining the weighted image signals

Digital image processing and display techniques utilizing differential image intensity determinations

Abstract: Techniques of image processing and display particularly adapted for use in thermography. A first heat image is digitized and stored. A second heat image is acquired, digitized and then compared point-by-point with that of the first image. Any differences in intensity between the two images are also stored. The difference data is used to display on a CRT an optical image of the thermal differences between the two images, thus allowing comparison of the heat radiant characteristics of one object with a standard, or such characteristics of an object at different times.

Histograms of Image Sequence Spectra

Abstract: We investigated histograms of the Fourier transform amplitudes of image sequence spectra Our results show that the Fourier amplitudes of images within the same sequence do not differ very much if the scenery in general remains the same throughout the sequence As a useful consequence of this diagnosis we replaced the Fourier amplitude of every image in the sequence by an estimate The estimate was obtained by averaging over the Fourier amplitudes of the first few images We reconstructed images from their correct Fourier phase and from the estimated Fourier amplitude This concept can be used in transform coding, where we can achieve a data compression of approximately 1/2

Direct Image Plane Deblurring

Abstract: We describe here a digital image restoration technique for image data degraded by an a-priori known blur function. To be more specific, we are interested in processing digital image data, obtained using coherent illumination (either optical or microwaves), that has been degraded by a known blur factor, The complex valued image i (amplitude) is related to the measured blurred data i by i = i * b, where * denotes convolution and b is a known complex-valued blur function. An inverse filtering technique is traditionally used in the Fourier domain. But, for some image analysis applications, a more direct, deblurring approach in the image domain may be more desirable. An illustrative possible scenario is given by an image interpreter looking at a small portion of some blurred image. In this case a direct deblurring method applied to the selected image area might be more flexible. We present here a direct image plane deconvolution method using reasonably short length convolution kernels. In the more specific case of quadratic phase-type blurs, a direct image plane Fresnel transform approach is also discussed.© (1983) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.