Tianxu Zhang

Efficient method for multiscale small target detection from a natural scene

According to the principle of human discrimination of small targets from a natural scene that there is a signature of discontinuity between the object and its neighboring regions, we develop an efficient method for multiscale small target detection using template matching based on a dissimilarity measure, which is called an average gray absolute difference maximum map (AGADMM), and infer the criterion of recognizing multiscale small objects from the properties of the AGADMM of the natural scene, which is a spatially independent and stable Gaussian random field. We explain how the AGADMM increases the ratio of the signal of object-to-background perturbations, improves the detectable probability, and keeps the false alarm probability very low. We analyze the complexity of computing an AGADMM and justify the validity and efficiency. Experiments with images of a natural scene such as a sky and sea surface have shown the great potential of the proposed method for distinguishing multiscale small objects from a natural scene.

Fast restoration approach for rotational motion blurred image based on deconvolution along the blurring paths

We present a novel approach to restoring images blurred by rotational motions, without experiencing geometric coordinate transformations as in traditional restoration. The space-variant blur is decomposed into a series of space-invariant blurs along the blurring paths. By incorporating Bresenhams algorithm into our work, the blurred gray values of the discrete pixels can be fetched along the blurring paths in real time. Thus, the space-variant blur can be quickly removed along the blurring paths. We apply a two-stage process to restore the rectangular blurred image, which results in the proposal of two corresponding restoration algorithms. One removes the blur by deconvolution along the blurring paths, which are completely inside the rectangular image. The other is used in the case when only some of the pixels of some blurring paths are inside the rectangular image, so based on a neighborhood knowledge guide, the information of these pixels is restored with the least cost in terms of the constrained optimization estimation theory. Furthermore, these two restoration algorithms avoid iteration calculations and some time-consuming operations. To determine the blur center and the blur extents from the blurred image in a case of not knowing the rotational motion parameters, we present, based on cross correlation, an effective blur identification method, which becomes an integral part of the proposed approach. The experimental results demonstrate the efficiency of the proposed restoration algorithms and the effectiveness of the blur identification method.

Moving weak point target detection and estimation with three-dimensional double directional filter in IR cluttered background

We assess the performance of a novel three-dimensional double directional filtering 3DDDF algorithm for detecting and tracking weak moving dim targets against a complex cluttered background in infrared IR image sequences. This proposed method increases the tar- get energy accumulation ability further than the three-dimensional direc- tional filter 3DDF method. Prior to the filtering, a new prewhitening method termed a three-dimensional spatialtemporal adaptive prediction filter TDSTAPF is used to suppress the cluttered background. Exten- sive experiment results demonstrate the proposed algorithms ability to detect weak dim point targets against a complex cloud-cluttered back- ground in real IR image sequence and the performance comparisons of the proposed method and 3DDF.

Liquid-crystal microlens with focus swing and low driving voltage

A focus-swing liquid-crystal (LC) microlens with two patterned electrodes and filled in nematic liquid crystal is proposed. In order to lower the level of the applied voltage signal and effectively increase the focus-swing range, the bottom electrode is designed as a circular patterned structure. The top electrode is composed of four stripe-patterned subelectrodes, which are powered, respectively to generate expecting potential and drive the focus swing in the focal plane of the microlens. The common optical properties of the LC microlens and the swing behavior of the formed focus in the focal plane are demonstrated experimentally.

Edge-directed adaptive nonuniformity correction for staring infrared focal plane arrays

An in-depth analysis is made in the case of object degeneration and ghosting artifacts in a neural-network-based nonuniformity correction algorithm (NN-NUC) for infrared focal plane arrays (IRFPAs). It is found that updating the correction coefficients blindly in the NN-NUC scheme without taking the object edge into account is the root of the problem. Based on this conclusion, an edge-directed NN-NUC scheme (ED-NN-NUC) is proposed to eliminate ghosting artifacts and object degeneration. Comparison experiments with simulated data and real IRFPA infrared data show that the root of the problem pointed out is correct and the proposed scheme is rational and effective.

Universal deblurring method for real images using transition region

In this paper, we present a universal deblurring method for real images without prior knowledge of the blur source. The proposed method uses the transition region of the blurred image to estimate the point spread function (PSF). It determines the main edges of the blurred image with high edge measures based on the difference of Gaussians (DoG) operator. Those edge measures are used to predict the transition region of the sharp image. By using the transition region, we select the pixels of the blurred image to form a series of equations for calculating the PSF. In order to overcome noise disturbance, the optimal method based on the anisotropic adaptive regularization is used to estimate the PSF, in which the constraints of non-negative and spatial correlations are incorpo- rated. Once the PSF is estimated, the blurred image is effectively recov- ered by employing nonblind restoration. Experimental results show that the proposed method performs effectively for real images with different blur sources.

Restoration algorithms for turbulence-degraded images based on optimized estimation of discrete values of overall point spread functions

For the problem of restoration of turbulence-degraded images, it is of utmost importance to make a correct estimation of the turbulence s stochastic point spread function (PSF). A new method is presented for estimating the discrete values of overall PSFs of turbulence-degraded images. For this method, two short-exposure turbulence-degraded images are used as the inputs, for which the Fourier transforms are made and a series of equations for calculating the discrete values of the turbulence PSFs are developed. Some effective rules for selecting equations have been worked out to ensure a reliable solution for the PSFs. To overcome the interference of noise, two optimization algorithms for estimating the turbulence PSF values, based on quadratic and nonquadratic regularization that can be incorporated into the estimation process, are proposed, in which the constraints of the PSF values are non-negative and smooth [quadratic regularization non-negative and smooth (QRNNS) and nonquadratic regularization non-negative and smooth (NQRNNS)]. A series of experiments are performed to test the algorithms proposed, which show that the NQRNNS algorithm is both rational and highly effective.

Characteristics of contrast and application for small-target detection

The detection of small targets, especially of a target within a single frame of data, is an important problem in image processing. A lot of work have already been proposed for this problem. Of them, nonlinear morphology-based methods have shown their advantages than traditional linear methods in target detection. Many of these methods are based on local background estimate and threshold computation. A thresholding procedure is required for the methods. However, none of them shows how to get an appropriate threshold and what is the relation between a threshold and the detection performance of the detector. In this paper, we use the contrast between target and local background to be the measurement of characteristic of targets and background. Here, the contrast between target and local background is the ratio of target residual, which is acquired by subtracting local background estimate from the original image, and local background estimate. By analyzing the difference between the contrast between target and local contrast between background and local background, we can determine an appropriate threshold which can achieve high probability of detection while produce very small probability of false alarm. Experiments on a large read sea- surface ship images prove the effectiveness of the method presented in this paper.

Development and characterization of an electrically tunable liquid-crystal Fabry–Pérot hyperspectral imaging device

A smart spectral imaging detection method based on the integration of an electrically tunable liquid-crystal Fabry–Pérot microstructure and a focal plane array is discussed. The layout of the spectral device is designed effectively and prototypes with working wavelengths in the range of 800 to 900 nm were fabricated using ultraviolet photolithography and wet etching. Measurements were carried out with careful analysis. Based on the results, this paper proposes a smart spectral imaging array device structure that can potentially obtain the image of many spectral bands simultaneously in one picture frame. Some key issues concerning such structures for imaging applications and calibration are discussed. Without any mechanical parts, this kind of spectral component exhibits some advantages such as low cost and compact integration.

Dual-band infrared remote sensing system with combined long-wave infrared imaging and mid-wave infrared spectral analysis

We present a new optical system for infrared (IR) image-spectrum integration remote sensing. The purpose to develop this instrument is to find the key spectral characteristics of typical hot target and to explore a new intelligence fusion method for the recognition. When mounted on a two-dimensional rotation stage, it can track the suspected target by image processing, and then get its spectrum to do recognition. It is a dual-band system with long-wave infrared (LWIR) imaging and mid-wave infrared (MWIR) spectrum. An IR dichroic beamsplitter is used to divide wideband incident infrared into LWIR and MWIR. Compared to traditional infrared combined imaging and spectral-analysis instruments, it yields higher sensitivity for measuring the IR spectrum. The sensors for imaging and spectrum detection are separate, so high spatial resolution, frame rate, and spectrum resolution can all be obtained simultaneously.