Reduction of blocking artifacts in both spatial domain and transformed domain

In this paper, we propose a bi-domain technique to reduce the blocking artifacts commonly incurred in image processing. Some pixels are sampled in the shifted image block and some high frequency components of the corresponding transformed block are discarded. By solving for the remaining unknown pixel values and the transformed coefficients, a less blocky image is obtained. Simulation results using the Discrete Cosine Transform and the Slant Transform show that the proposed algorithm gives a better quantitative result and image quality than that of the existing methods

A note on parallel and pipeline computation of fast unitary transforms

The parallel and pipeline organization of fast unitary transform algorithms such as the Fast Fourier Transform are discussed. The efficiency is pointed out of a combined parallel-pipeline processor of a transform such as the Haar transform in which 2 to the n minus 1 power hardware butterflies generate a transform of order 2 to the n power every computation cycle

Recognition and reconstruction of coherent energy with application to deep seismic reflection data

Reflections in deep seismic reflection data tend to be visible on only a limited number of traces in a common midpoint gather. To prevent stack degeneration, any noncoherent reflection energy has to be removed. In this paper, a standard classification technique in remote sensing is presented to enhance data quality. It consists of a recognition technique to detect and extract coherent energy in both common shot gathers and fi- nal stacks. This technique uses the statistics of a picked seismic phase to obtain the likelihood distribution of its presence. Multiplication of this likelihood distribution with the original data results in a “cleaned up” section. Application of the technique to data from a deep seismic reflection experiment enhanced the visibility of all reflectors considerably. Because the recognition technique cannot produce an estimate of “missing” data, it is extended with a reconstruction method. Two methods are proposed: application of semblance weighted local slant stacks after recognition, and direct recognition in the linear tau-p domain. In both cases, the power of the stacking process to increase the signal-to-noise ratio is combined with the direct selection of only specific seismic phases. The joint application of recognition and reconstruction resulted in data images which showed reflectors more clearly than application of a single technique

Atmospheric Trace Molecule Spectroscopy (ATMOS) experiment version 3 data retrievals

Version 3 of the Atmospheric Trace Molecule Spectroscopy (ATMOS) experiment data set for some 30 trace and minor gas profiles is available. From the IR solar-absorption spectra measured during four Space Shuttle missions (in 1985, 1992, 1993, and 1994), profiles from more than 350 occultations were retrieved from the upper troposphere to the lower mesosphere. Previous results were unreliable for tropospheric retrievals, but with a new global-fitting algorithm profiles are reliably returned down to altitudes as low as 6.5 km (clouds permitting) and include notably improved retrievals of H2 O, CO, and other species. Results for stratospheric water are more consistent across the ATMOS spectral filters and do not indicate a net consumption of H2 in the upper stratosphere. A new sulfuric-acid aerosol product is described. An overview of ATMOS Version 3 processing is presented with a discussion of estimated uncertainties. Differences between these Version 3 and previously reported Version 2 ATMOS results are discussed. Retrievals are available at http: /atmos.jpl.nasa.gov /atmos

Fast Mojette Transform for Discrete Tomography

A new algorithm for reconstructing a two dimensional object from a set of one dimensional projected views is presented that is both computationally exact and experimentally practical. The algorithm has a computational complexity of O(n log2 n) with n = N^2 for an NxN image, is robust in the presence of noise and produces no artefacts in the reconstruction process, as is the case with conventional tomographic methods. The reconstruction process is approximation free because the object is assumed to be discrete and utilizes fully discrete Radon transforms. Noise in the projection data can be suppressed further by introducing redundancy in the reconstruction. The number of projections required for exact reconstruction and the response to noise can be controlled without comprising the digital nature of the algorithm. The digital projections are those of the Mojette Transform, a form of discrete linogram. A simple analytical mapping is developed that compacts these projections exactly into symmetric periodic slices within the Discrete Fourier Transform. A new digital angle set is constructed that allows the periodic slices to completely fill all of the objects Discrete Fourier space. Techniques are proposed to acquire these digital projections experimentally to enable fast and robust two dimensional reconstructions.Comment: 22 pages, 13 figures, Submitted to Elsevier Signal Processin

Computed tomography from X-rays: old 2-D results, new 3-D problems

We consider old results on 2-D computerized tomography methods and their relevance to new fully 3-D problems. We examine the 2-D filtered back-projection method (FBP) from several perspectives to better understand how it works. Based on that understanding, we question whether stable, reliable reconstruction algorithms can be found for wide-detector cone-beam 3-D machines with their resulting large-slant beams. We use a numerical method of "point response function fitting" to compute convolution kernels H(u, v) (for use with back-projection) for a model slant-beam problem. These kernels exhibit disturbing growing and spreading oscillations which would greatly amplify errors in the projection data

Shape from periodic texture using the eigenvectors of local affine distortion

This paper shows how the local slant and tilt angles of regularly textured curved surfaces can be estimated directly, without the need for iterative numerical optimization, We work in the frequency domain and measure texture distortion using the affine distortion of the pattern of spectral peaks. The key theoretical contribution is to show that the directions of the eigenvectors of the affine distortion matrices can be used to estimate local slant and tilt angles of tangent planes to curved surfaces. In particular, the leading eigenvector points in the tilt direction. Although not as geometrically transparent, the direction of the second eigenvector can be used to estimate the slant direction. The required affine distortion matrices are computed using the correspondences between spectral peaks, established on the basis of their energy ordering. We apply the method to a variety of real-world and synthetic imagery