МЕТОД СТИСНЕННЯ ДАНИХ ДИФРАКЦІЙНИХ ТА ІНТЕРФЕРЕНЦІЙНИХ ЗОБРАЖЕНЬ

In the paper the diffraction and interference images received by numerical simulation and experimentally in solving fundamental and applied problems of photonics. Images are structures with a special intensity distribution formed by the initial field and the optical system. To increase the speed of processing of the image data compression method with further implementation in databases is developed. The method of diffraction and interference images compression is based on the intensity quantization. An algorithm for image quantization has been developed: target intensity values have been determined, which allow setting quantization levels, and data visualization techniques, which determine the threshold values for these levels. The algorithm also contains image segmentation by the size of the minimum size of the topological object. The vicinity of topological object is defined under the conditions of a visual registration form and do not crossing with other regions. The topological objects of the diffraction field determine as the maximum, minimum and zero intensity, and in the interference pattern such topological objects are the maximum, minimum and the region of the band splitting. Important parameters are the average value of the intensity of the whole image - which highlights its overall structure and the average value of the intensity of the local segment. The following results were obtained by compressing data from an 8-bit image in grayscale to 2 bits of color depth are enough for an interference image, and to 3 bits, which are enough for a diffraction image. The quantization differences for diffraction images and interference patterns are shown. Data compression ratios are calculated. On the one hand, the application of the obtained results and recommendations is possible in various fields of medicine, biology and pharmacy , which use laser technology, and on the other hand in the development of separate IT identification of topological objects in the light field, optical image processing and decision support in optical problems.

A 13.3 Gbps 9/7M Discrete Wavelet Transform for CCSDS 122.0-B-1 Image Data Compression on a Space-Grade SRAM FPGA

Remote sensing is recognized as a cornerstone monitoring technology. The latest high-resolution and high-speed spaceborne imagers provide an explosive growth in data volume and instrument data rates in the range of several Gbps. This competes with the limited on-board storage resources and downlink bandwidth, making image data compression a mission-critical on-board processing task. The Consultative Committee for Space Data Systems (CCSDS) Image Data Compression (IDC) standard CCSDS-122.0-B-1 is a transform-based 2D image compression algorithm designed specifically for use on-board a space platform. In this paper, we introduce a high-performance architecture for a key-part of the CCSDS-IDC algorithm, the 9/7M Integer Discrete Wavelet Transform (DWT). The proposed parallel architecture achieves 2 samples/cycle while the very deep pipeline enables very high clock frequencies. Moreover, it exploits elastic pipeline principles to provide modularity, latency insensitivity and distributed control. The implementation of the proposed architecture on a Xilinx Kintex Ultrascale XQRKU060 space-grade SRAM FPGA achieves state-of-the-art throughput performance of 831 MSamples/s (13.3 Gbps @ 16bpp) allowing seamless integration with next-generation high-speed imagers and on-board data handling networking technology. To the best of our knowledge, this is the fastest implementation of the 9/7M Integer DWT on a space-grade FPGA, outperforming previous implementations.