This paper introduces a new iterative image restoration method which is capable of restoring noisy, blurred images by incorporating a priori knowledge about the image and noise statistics into the iterative procedure....
详细信息
This paper introduces a new iterative image restoration method which is capable of restoring noisy, blurred images by incorporating a priori knowledge about the image and noise statistics into the iterative procedure. The iteration equation consists of a prediction part which is based on a noncausal image model description and an innovation part which is weighted by a gain factor. The gain is computed using a linear MSE optimization procedure and is updated at each step of the iteration. This image restoration scheme can be interpreted as an iterative procedure with a statistical constraint on the image data.
Several estimators for the digital restoration of a noisy image are presented. These estimators differ from those previously found in the literature in that they are robust for deviations from the assumed signal or no...
详细信息
Several estimators for the digital restoration of a noisy image are presented. These estimators differ from those previously found in the literature in that they are robust for deviations from the assumed signal or noise statistics, and the image is assumed to have been corrupted by signal-dependent or nonlinear noise, rather than simple additive noise. The assumption of signal-dependence complicates the problem considerably for non-robust estimators; for robust estimators, the problems are such that analytic solutions become impossible, and numerical methods must be used to derive the estimators. Both point-estimators and multi-parameter estimators are considered. In addition to the description of the various robust estimators, a comparison of their performance on real images corrupted by simulated signal-dependent noise with various (Gaussian and non-Gaussian) distributions is also presented.
A unified theoretical treatment of constrained optimisation methods for tomographic and spectral estimation from discrete data is given. The solution is shown to be equivalent to the unconstrained optimisation of a du...
详细信息
A unified theoretical treatment of constrained optimisation methods for tomographic and spectral estimation from discrete data is given. The solution is shown to be equivalent to the unconstrained optimisation of a dual functional in which the image or spectrum is modelled in terms of a Lagrange multiplier vector and the kernel of the constraint integrals. In order to obtain the best possible solution it is important to consider the effects of noise in the constraints. The problem is reformulated using the above models and the exact data is replaced with the noise statistics as constraints; this is solved using a penalty method. A very fast direct algorithm is also introduced which matches the noise variance provided the signal to noise ratio is approximately known.
The coherent optical filtering techniques provide a general concept for the classification of patterns. This paper describes the design and testing of a hybrid optical-digital imageprocessing system and the developme...
详细信息
statisticalmethods for estimating the parameters of a system are often based on assuming that the system inputs are Gaussian. As a result least-squares criteria are commonly used for estimating the system parameters....
详细信息
statisticalmethods for estimating the parameters of a system are often based on assuming that the system inputs are Gaussian. As a result least-squares criteria are commonly used for estimating the system parameters. In this paper we will describe methods that are based on uniformly distributed system inputs. The estimates of the system parameters will then be found from min/max operations on linear combinations of the output samples. A new method for solving the resulting min/max problems is described and the min/max criterion is used in an application where it performs better than the commonly used least-squares criterion.
In this paper Mendel and Hsueh's [10] state-variable modeling technique for transforming a 1-D non-causal system into a causal system is extended to 2-dimensional systems which have half-plane (HP) supports. The 2...
详细信息
In this paper Mendel and Hsueh's [10] state-variable modeling technique for transforming a 1-D non-causal system into a causal system is extended to 2-dimensional systems which have half-plane (HP) supports. The 2-D impulse responses treated here are restricted to a class in which their associated 2-D z-transforms have separable denominators. The final state space model is a special type of so-called Roesser's model. It is a very low-order model, which is important from a computational point of view, when, for example, 2-D recursive estimation algorithms are applied to 2-D systems with HP supports.
A model for the reconstruction of real color textures is presented. It is an extension of a bidimensionnal Markov model previously proposed for the synthesis of gray level textures. The main problem is to limit the nu...
详细信息
A model for the reconstruction of real color textures is presented. It is an extension of a bidimensionnal Markov model previously proposed for the synthesis of gray level textures. The main problem is to limit the number of colors to avoid computationnal complexity. This is solved by operating a suboptimal quantization of the color information included in the real texture: i) firstly by transforming the color components into a perceptive uniform space, based on a vision model; ii) then by optimally clustering this color space.
The stochastic modeling aspects of image restoration are considered for 2-D nonstationary processes. We develop a space variaflt Roesser madel for such processes, a d deyive prnY&xres for stocha5tic identification...
详细信息
The stochastic modeling aspects of image restoration are considered for 2-D nonstationary processes. We develop a space variaflt Roesser madel for such processes, a d deyive prnY&xres for stocha5tic identification ard estimation in the context of a v i s u a l q u a l i t y c r i t e r i a n .
To develop a method of automatic hip prothesis design, it is necessary to achieve a detection of the edges of the medullary canal of the femur, from X-ray images. The procedure of the pattern recognition of the medull...
详细信息
To develop a method of automatic hip prothesis design, it is necessary to achieve a detection of the edges of the medullary canal of the femur, from X-ray images. The procedure of the pattern recognition of the medullary canal is described. It uses a statistical detector of change in level in a white noise and a bayesian estimation of a step signal in an autoregressive noise.
This paper is concerned with reversible seismic data compression techniques for transmitting data from exploration field to a research center via satellite. The statistical character istics of seismic data, including ...
详细信息
This paper is concerned with reversible seismic data compression techniques for transmitting data from exploration field to a research center via satellite. The statistical character istics of seismic data, including Vibroseis data and impulsive data, are examined. Based on these characteristics, various compression techniques, including prediction, orthogonal transforms, and digital coding methods have been investigated. Explicit methods are proposed for compressing the Vibroseis and impulsive data. These methods have been simulated for extensive real data. The compression performance is measured by the compression ratio and the signal-to-noise ratio. The results indicate that a compression ratio ranging between five to one and six to one with at least a 30 dB SNR can be achieved. Facts of real-time design that is, execution time, core size requirement, depth of queue, and transmission time are examined. For transmitting the compressed seismic data using a 7-bit block counter with continuous ARQ, 5000 bits per frame are recommended for a 9600 bps channel bandwidth.
暂无评论