Qi He Hong

Ringing artifact reduction for Poisson MAP superresolution algorithms

The distribution of edge values for an image of a general scene often has a sharp peak with a long tail. This property, which can be well described by a Lorentzian probability function, has been used to introduce a correction term that reduces the ringing artifacts that are associated with the Poisson MAP superresolution methods.<<ETX>>

Removing line patterns from infrared and passive millimeter wave images

This paper is concerned with removing a typical noise artifact: the line patterns that arise from the use of parallel detector channels in an imager. There is an advantage in using a number of parallel scanned radiometers in order to reduce the frame time of an imager, but the response of these channels tends to be non-uniform and produces regular scan lines in the image. This effect may conceal important image details and reduce the signal to noise ratio in the image with the result that image restoration algorithms are not as effective as they could be. A number of efficient methods have been developed to remove these scan lines, either in real space or in the Fourier domain. These techniques can be applied to both infrared and millimeter wave systems and their effectiveness has been demonstrated by practical examples.

Measurement of the MTF and MRTD for focal plane arrays

The use of focal plane arrays (FPAs) in infrared imaging systems is becoming increasingly important. There are problems, however, in measuring their modulation transfer function (MTF) and their minimum resolvable temperature difference (MRTD) since these performance measures vary with the exposition of the image on the FPA. This limitation has been overcome through the introduction of a discrete MTF for these imaging systems using discrete Fourier transform techniques. This discrete MTF is a unique function of spatial frequency and has been measured using a microscanned discrete line spread function. It has also formed the basis of an objective MRTD, the results of which have been compared with subjective measurements.

Overview of recent advances in passive millimeter-wave imaging in the UK

Passive millimeter wave (MMW) imaging systems have attracted an increasing interest over the past years due to their superior poor weather performance compared with visible and infrared (IR) systems. In the UK the Defence Research Agency Malvern developed its first MMW radiometers in the late 1950s. These systems were bulky and had poor spatial resolution and low thermal sensitivity, but the considerable advances in semiconductor solid state devices have allowed the size and weight of images to be reduced. Advantage can also be taken of sophisticated on-line signal processing and of complex theoretical modeling and analysis. This paper examines the impact of these advances of technology and to identify new methods to overcome the usual difficulties of poor spatial resolution and slow response time. High quality images are presented to demonstrate the potential of this emerging technology.

Superresolution by spatial-frequency aliasing

A super-resolution scheme based on the use of a sampling grating has been proposed to extend the spatial resolution of an IR imager operating in the 8 - 14 micrometer spectral region, where there are at present technological difficulties in manufacturing large arrays of photon detectors. An intrinsic property associated with any sampling device is the aliasing effect which transfers the higher spatial frequency content of the scene down onto the lower frequency regions. While this property is regarded as a problem for many image processing algorithms, it is used in this paper as a spatial frequency encoding technique which enables all the spatial frequency information of the scene to pass through the imaging system. A new higher resolution image is then reconstructed from a series of images obtained with the grating in a series of different positions. This method is illustrated by computational and experimental simulations and is compared with super- resolution algorithms based on inverse transform techniques.

Bandwidth extension for IR detectors through spatial-frequency shifting

We describe a new scheme for extending the bandwidth of IR detectors by the employment of a reticle that shifts the higher spatial-frequency content of the scene onto the lower-frequency region. Then all the spatial-frequency information can pass through the bandwidth of the detector system, so that a high-resolution image may be reconstructed from a series of pictures obtained with the reticle in a number of predetermined positions.

Nonlinear image restoration algorithm with artifact reduction

The distribution of edge values for an image of a general scene often has a sharp peak with a long tail. This property which can be well described by a Lorentzian probability function has been used to develop an efficient non-linear image restoration algorithm for reducing the various artifacts that often arise in the restored images. The algorithm starts with a Wiener filter solution which is used to model the edge image by the Lorentzian function so that the likelihood of the image can be estimated. A non-linear correction term is then introduced which increases this image likelihood under the mean square error (MSE) criterion. This process ensures that the resulting image retains its sharpness while reducing the noise and ringing artifacts. An iterative procedure has been developed to implement this method. Computer simulated results show that the algorithm is robust in reducing artifacts and easily implemented. The algorithm also possesses a superresolution capability due to the highly nonlinear property of the correction term.

Comparison of methods for super-resolving passive millimeter wave images

We present our results to date on the application of super- resolution techniques to passive millimeter-wave imagery and discuss the merits of both linear and non-linear methods giving an indication of the improvement which can be obtained. Passive millimeter-wave imagery is potentially useful where poor weather visibility is required. Its spatial resolution, however, is severely restricted due to the diffraction limit of the optics. Super-resolution methods may be used to increase this spatial resolution but often at the expense of processing time. Linear methods may be implemented in real time whereas non-linear methods which are required to restore images with lost spatial frequencies are more time consuming. There is clearly a trade-off between resolution and processing time. In order to make any useful comparisons it is necessary to quantify any improvements, we do this by investigating the resolution and spatial frequency content of the images. We have applied our super-resolution algorithms to conventional images as well as millimetric bar pattern images which were acquired at 94 and 140 GHz. These methods give excellent results, providing a significant quantifiable increase in spatial resolution with only a small reduction in the final signal to noise ratio. Comparisons will be made between the results obtained with various super-resolution algorithms.

Antialiasing algorithm for focal plane arrays

The use of focal plane arrays introduces an aliasing problem which transfers higher spatial frequencies onto lower frequency regions and restricts the available spatial resolution or field of view. An anti-aliasing interpolation algorithm has been developed to improve this spatial resolution. The image is initially expanded to the required size with a usable lower frequency region which contains the aliased higher frequency components. A maximum likelihood criterion is then applied to estimate this higher frequency information based on a statistical image model, so that the aliasing effect can be reduced.

Interpolator for infrared images

The use of focal plane arrays in IR imaging systems is becoming increasingly important, but in the long-wave IR region the number of detector elements in the array is limited by the current state of technology, and this in turn restricts the available spatial resolution or field of view. An image processing scheme is described that is able to interpolate and enhance an image in a unified moving window operation. The image is first expanded to the required size by pixel replication and then processed so that the resulting spectrum approximates that of the original scene. A numerical method has been developed to calculate the interpolator and its use has been demonstrated in a computer simulation.