Method and system for processing VGA-format image

Abstract

The invention provides a method and system for processing a VGA-format image. The system comprises an image sensor, a source data storage device and a microcontroller, wherein the image sensor is used for collecting source data of the VGA-format static image, the input end of the source data storage device is connected with the image sensor, the source data storage device is used for storing the source data, the input end of the microcontroller is connected with the output end of the source data storage device, and the microcontroller is used for reading the single-line source data in a line-by-line mode, sequentially carrying out interpolation operation and compression processing on the single-line source data in a line-by-line mode, finally generating single-line imaging data, and outputting the single-line imaging data in a line-by-line mode. By means of the method and system for processing the VGA-format image, the image quality and the image data number are balanced, the low cost and the applicability of the method and system are reflected, the performance of the Internet of Things can be improved when the method and system are applied to image collecting nodes of the Internet of Things, and the Internet of Things can be easily applied and popularized.

Description

technical field [0001] The invention relates to the technical field of image processing, in particular to a method and system for processing VGA format images. Background technique [0002] With the development of Internet and Internet of Things technology, there is a greater demand for image data collection, compression, storage, and transmission, especially the rise of Internet of Things technology, which has higher requirements for the processing of node image data. In the prior art, the processing of image data is basically divided into two methods: the first method is that the acquisition, compression, and storage of image data are completely realized by hardware dedicated to image processing. The advantage of this method is that the processing The speed is fast, but it also has the disadvantages of poor tailorability and high price; the second method is composed of two parts: hardware and software. The hardware part includes a micro-processing unit, an image photosens...

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Problems solved by technology

In the prior art, the processing of image data is basically divided into two methods: the first method is that the acquisition, compression, and storage of image data are completely realized by hardware dedicated to image processing. The advantage of this method is that the processing The speed is fast, but it also has the disadvantages of poor tailorability and high price; the second method is composed of two parts: hardware and software. The hardware part includes a micro-processing unit, an image photosensitive processing unit, a storage unit and a transmission unit. The source data generally has a large amount of data, such as 100,000-pixel CIF format (352*288, about 100KB of single-frame data), 300,000-pixel VGA format (640*480, about 300KB of single-frame data), and 1.3 million-pixel SVGA format (1280*1024, single frame data is about 1300KB), the higher the pixel, the greater the amount of data. Therefore, for image processing, it is generally required that the micro-processing unit has a higher main frequency and the storage unit has a larger capacity. The software part is mainly for The image data is compressed to a certain extent to be suitable for network transmission. At present, the micro-processing unit using the second method to process images is mostly DSP, and the storage unit uses extended SDRAM (generally above 4MB). This image processing device The advantage is that the acquisition and processing speed is fast, and it is suitable for high-pixel image photosensitive processing units. The disadvantage is that the price is relatively high, and the general cost is more than 200 yuan. In the Internet of Things, the requirements for the image pixels collected are not very high, generally 300,000 Pixel VGA format images are sufficient to meet the requirements of most devices, so for the application of multi-node image acquisition in the Internet of Things, the high cost of nodes is not conducive to the promotion and application of the Internet of Things

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