Investigation of the image resampling requirements of remote sensing has indicated a need for improved resampling convolution kernel design. Areas in which progress has been made include a recognition of the improved phase linearity of longer kernels and the need for similarity of the modulation transfer function (MTF) across all filters. The computational capability required for the longer kernels is achieved with a dedicated signal processor.

High-fidelity Image Resampling For Remote Sensing

Band-to-band coregistration of multispectral remote sensing images can be achieved by electronic signal processing techniques rather than by costly and difficult mechanical alignment. This paper describes the results of a study of the end-to-end performance of electronic registration. The software simulation includes steps which model the performance of the geometric calibration process, the instrument image quality, detector performance and the effects of achieving coregistration through image resampling. The image resampling step emulates the Pipelined Resampling Processor, a real-time image resampler. The study demonstrates that the electronic alignment technique produces multispectral images which are superior to those produced by an imager whose pixel geometry is accurate to 0.1 pixel rms. The implications of this approach for future earth observation programs are discussed.

Simulation of electronic registration of multispectral remote sensing images to 0.1 pixel accuracy

A new method of image coordinates transformation is suggested, it is based on the preliminary complexity calculation of transformed images, extraction and transformation only of coordinates highly informative part. The ways of realization of the proposed method using different computer means are being considered. The structure of optical-electronic system, that combines algorithmic flexibility of an ordinary computer and high speed of images preprocessing with the help of optical means, is being suggested.© (1993) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Method of adaptive image coordinate transformation

Digital reconnaissance images gathered by low-altitude over-flights with resolutions on the order of a few feet and fields of view up to 120 degrees can generate millions of pixels per second. Storing this data in-flight, transmitting it to the ground, and analyzing it presents significant problems to the tactical community. One potential solution is in-flight preview and pruning of the data where an operator keeps or transmits only those image segments which on first view contain potential intelligence data. To do this, the images must be presented to the operator in a geometrically correct form. Wide-angle dis-tortion, distortions induced by yaw, pitch, roll and altitude variations, and distortions due to non-ideal alignment of the focal plane array must be removed so the operator can quickly assess the scene content and make decisions on which image segments to keep. When multiple sensors are used with a common field of view, they must be mutually coregistered to permit multispectral or multimode processing to exploit these rich data dimensions. In addition, the operator should be able to alter the apparent point of view of the image, i.e., be able to zoom in and out, rotate, and roam through the displayed field of view while maintaining geometric and radiometric precision. These disparate requirements have a common feature in the ability to perform real-time image geometry manipulation. The role of image geometry manipulation, or image warping, is reviewed and a "strawman" system dis-cussed which incorporates the Pipelined Resampling Processor (PRP). The PRP is a real-time image warping processor discussed at this conference in previous years"2'3". Actual results from the PRP prototype are presented. In addition, other image processing aids such as image enhancement and object classification are discussed as they apply to reconnaissance applications.

Management Of Airborne Reconnaissance Images Through Real-Time Processing

The Pipelined Resampling Processor (PRP) was presented to this conference in 1983 in concept as a practical solution to real-time high resolution geometric image rectification needs. In the present report we present performance results obtained from the PRP development unit completed in late 1983. The small size, weight, and power requirements of the PRP and its high throughput make it very well suited for space and airborne applications where goemetric correction of image data must be done autonomously in real-time. This high resolution geometric correction is a necessary adjunct to applications using frame differencing or frame averaging for motion compensation, moving target indication, noise suppression or data compression as well as applications requiring precise correction of focal plane sampling distortions. By equipping the PRP with manual controls, image geometry can be manipulated at video rates from a console to achieve a much higher image analysis throughput than is possible for more general purpose processing facilities. In mapping, merging, classifi-cation and registration applications, interactive video rate processing will be important in bringing these and other image analysis techniques out of the laboratory and into an operational environment.

Art Gabriel

Papers

The Pipelined Resampling Processor: Performance Of A Development Unit Which Is Applicable To A Wide Range Of Real-Time Imaging Applications