Frequency domain astronomical image target detection method and system

Abstract

The invention discloses a frequency domain astronomical image target detection method and system, and the method is realized based on a CPU-GPU heterogeneous processor, and the method comprises the steps of carrying out the preprocessing of a collected original astronomical image through a CPU based on a reference image obtained in advance; respectively carrying out image partitioning on the reference image and the preprocessed astronomical image by adopting an overlapping storage method, multiplying a Gaussian basis function by a polynomial to obtain n groups of basis vectors of a convolution kernel, and inputting the n groups of basis vectors into a GPU; enabling the GPU to perform fitting according to the reference sub-images and the astronomical sub-images in combination with n groups of base vectors to obtain a convolution kernel corresponding to each reference sub-image, using the convolution kernels for performing frequency domain filtering blurring processing on each reference sub-image to obtain a template image, and inputting the template image into the CPU; and discarding the edge of the template image by the CPU, connecting the remaining parts and making a difference between the remaining parts and the original astronomical image to obtain a difference image, thereby realizing target detection of the astronomical image.

Description

technical field [0001] The invention belongs to the field of target detection, and relates to a frequency-domain astronomical image target detection method and system, which can be used in a space-borne embedded system. Background technique [0002] Among the space science and exploration missions announced by my country's space development plan, many tasks have a great impact on spacecraft artificial intelligence control, autonomous navigation and control, real-time on-orbit processing speed, storage data throughput, massive data processing, complex scientific calculations, and image processing. etc. have put forward urgent demands. Especially for deep space missions, due to the limitation of communication delay and bandwidth, for example, the communication delay to Mars is usually 20 minutes and the bandwidth is 250kbps, and the communication delay to Jupiter is 2 hours and the bandwidth is 120kbps. Raw data cannot all be transmitted back to the ground, so higher requireme...

AI Technical Summary

Problems solved by technology

Although the application of GPU in time-domain astronomy has greatly improved the data processing capability, it cannot fundamentally solve the problem of real-time data acquisition. Data processing mode in which the data is transmitted to the ground and then processed on the ground

Faced with more and more astronomical data, this traditional data processing mode is time-consuming and laborious. However, if part of the data processing and screening work can be performed on the satellite, redundant information can be filtered, and valuable observation information can be extracted and downloaded. For the ground, this can not only greatly improve the real-time performance of information acquisition, but also improve the level of intelligent information processing on the star and reduce the pressure of data transmission between the star and the ground.

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