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Showing papers on "Iterative reconstruction published in 1970"


Journal ArticleDOI
Dorian Kermisch1
TL;DR: A quantitative analysis of the effect on image reconstruction of discarding the amplitude information contained in a wavefront reflected by a diffusely reflecting, coherently illuminated surface is given.
Abstract: A quantitative analysis of the effect on image reconstruction of discarding the amplitude information contained in a wavefront reflected by a diffusely reflecting, coherently illuminated surface is given. The image reconstruction from a phase record alone is analyzed for the perfect and imperfect phase-matching cases.

78 citations


Journal ArticleDOI
Y. Aoki1
TL;DR: In the process of reconstructing images from sound-wave holograms, optical and numerical reconstructions are investigated and the images reconstructed by the optical and the numerical methods are compared and discussed.
Abstract: Sound-wave holograms are constructed with sound waves of 10 kHz to 20 kHz by two holographic techniques; the coherent background and the electronic reference methods. The acoustical fields, which are scanned by a microphone and displayed by a lamp, are recorded on films as sound-wave holograms. In the process of reconstructing images from sound-wave holograms, optical and numerical reconstructions are investigated. In the optical reconstruction the images are reconstructed by illuminating the reduced hologram with laser light. The images reconstructed from grating-like holograms constructed in sampling-type holography are discussed. The numerical reconstruction of images is conducted by computer calculation of the digital Fresnel transform of sound-wave holograms using the FFT (fast Fourier transform) method. The analog sound-wave holograms recorded on films are divided into meshes of 64 × 64 cells and each cell is digitized into three levels according to the transparency of the film. The images reconstructed by the optical and the numerical methods are compared and discussed. Theoretical analyses are conducted to explain the experimental procedures and the obtained results.

21 citations


Journal ArticleDOI
01 Dec 1970
TL;DR: An iterative clustering technique is introduced; the procedure suboptimally minimizes the probability of differences between the binary reconstructions from the cluster codes and the original binary data.
Abstract: In many remote sensing applications millions of measurements can be made from a satellite at one time, and many times the data is of marginal value. In these situations clustering techniques might save much data transmission without loss of information since cluster codes may be transmitted instead of multidimensional data points. Data points within a cluster are highly similar so that interpretation of the cluster code can be meaningfully made on the basis of knowing what sort of data point is typical of those in the cluster. We introduce an iterative clustering technique; the procedure suboptimally minimizes the probability of differences between the binary reconstructions from the cluster codes and the original binary data. The iterative clustering technique was programmed for the GE 635 KANDIDATS (Kansas Digital Image Data System) and tested on two data sets. The first was a multi-image set. Twelve images of the northern part of Yellowstone Park were taken by the Michigan scanner system, and the images were reduced and run with the program. Thirty-thousand data points, each consisting of a binary vector of 25 components, were clustered into four clusters. The percentage difference between the components of the reconstructed binary data and the original binary data was 20 percent. The second data set consisted of measurements of the frequency content of the signals from lightning discharges. One hundred and thirty-four data measurements, each consisting of a binary vector of 32 components, were clustered into four clusters.

7 citations


Journal ArticleDOI
01 Jan 1970
TL;DR: Comparisons of two PWS filters in both frequency and spatial domain under several image types show that the spatial domain HPWS filter offers the best performance when the authors apply to restore object image, but this filter not successful in terms of memory usage and complexity of computation.
Abstract: Due to many factors that can be degraded an image quality from the desired version. Image reconstruction application is the method that aims to recover those degradations based on mathematical and statistical models. Partition-based weighted sum (PWS) filtering is one of the most effective techniques for application of an image restoration and reconstruction. In this paper, we compare two PWS filters in both frequency and spatial domain under several image types. Two PWS filters include hard partitionbased weighted sum (HPWS) filter and subspace hard partition-based weighted sum (S-HPWS) filter. Five image types are considered including aerial images, human images, miscellaneous images, object images and text images. The simulation results show that the spatial domain HPWS filter offers the best performance when we apply to restore object image, but this filter not successful in term of memory usage and complexity of computation. Frequency domain S-HPWS filter, which required less memory and computation time using PCA technique to reduce size of data, offers good performance when we attempt to restore miscellaneous image. On the other hand, text image gets poor performance from all types of filters.

3 citations


Journal ArticleDOI
TL;DR: In this paper, an unambiguous decoding method is described for reconstructing acoustic hologram images using an electronic means which avoids multiple image formation using an array of transducers along only the two axes, instead of over the entire hologram surface as is customary.
Abstract: A method is described for reconstructing acoustic hologram images using an electronic means which avoids multiple image formation. When the dimensions of the hologram are small compared to the dimensions of the viewing area, the incident waves are approximately plane rather than spherical. In this case the wavefront pattern can be resolved into components along two orthogonal directions, e.g., the x and y axes. Thus the information can be received by an array of transducers along only the two axes, instead of over the entire hologram surface as is customary. A disadvantage which occurs with reconstruction from plane waves is an ambiguity between right and left, resulting in the formation of multiple images. This effect may be avoided if the usual method of forming a diffraction pattern at the hologram surface by adding a reference wave is not carried out. Instead, the information is received and processed at the sound frequency f 0 . Spatial sine (V s ) and cosine (V c ) transforms are carried out first, and then demodulated. The essence of the unambiguous decoding method is to demodulate V s and V c by both in-phase and quadrature demodulation, forming four quantities which can be combined to give the required intensity. The combination of the four quantities is performed such as to effectively phase out the information from all directions except one and this avoids the formation of multiple images. The procedure is to be applied to both x and y axis information and the results multiplied to give a single reconstructed image.

2 citations


Proceedings ArticleDOI
01 Jan 1970

1 citations


Journal ArticleDOI
TL;DR: Theory and experiment show that for a hologram object of two or more object points, the nonlinearity of the photographic process causes reconstructed images in addition to both the desired reconstructed image and the higher order reconstructed images.
Abstract: Theory and experiment show that for a hologram object of two or more object points, the nonlinearity of the photographic process causes reconstructed images in addition to both the desired reconstructed image and the higher order reconstructed images. It is theoretically and experimentally shown that for a plane object parallel to the hologram plane, some of these undesired images may be focused in the plane of the desired reconstructed image.

1 citations


Journal ArticleDOI
01 Jan 1970
TL;DR: In order to reduce and constraint the space of reconstructed image, the frequency domain Tikhonov regularization technique is employed and it is shown that the quality of the reconstructed image is much better compared to the traditional algorithm under the noisy environment.
Abstract: In these recent years, Compressive Sensing (CS) is becoming an attractive topic in the field of Information Theory. It is widely used in several area including networking, image processing and digital camera. In particular, image reconstruction based on small number of measured components is known as the most useful application. In this paper, SL0 algorithm is specially used for the reconstruction process. It significantly decrease the processing time by utilizing a matrix in which the number of row is much smaller than number of column. Therefore, SL0 is known as one of the fastest and most accurate algorithm in CS. However due to ill-posed condition, if the prior information of the original image is undetermined, the reconstruction procedure of SL0 is much affected by the noise. Unfortunately, the investigation for solving this SL0 ill-posed condition is very limited therefore SL0 is not widely applied in many application. Consequently, this paper proposes a novel regularization technique for SL0 algorithm in the frequency domain. In order to reduce and constraint the space of reconstructed image, the frequency domain Tikhonov regularization technique is employed. It is shown that the quality of the reconstructed image is much better compared to the traditional algorithm under the noisy environment. The experimental result is exclusively simulated for 3 images: Lena, Sussie and Cameraman under both Gaussian and Non-Gaussian noise models (such as AWGN, Poisson noise, Salt & Pepper noise and Speckle noise) at different noise powers.

1 citations