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首页> 外文会议>Proceedings of the 2016 IEEE International Conference on Wireless Communications, Signal Processing and Networking >Filtering of Gaussian filter based embedded enhancement technique for compressively sensed images
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Filtering of Gaussian filter based embedded enhancement technique for compressively sensed images

机译：基于高斯滤波器的嵌入式增强技术对压缩图像的滤波

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Compressed sensing (CS) is the technique used in signal processing for acquiring and reconstructing a signal efficiently, by finding solutions to undetermined linear systems. In compressed sensing, the data is compressed and converted into fewer measurements at the transmitter end and are transmitted through the wireless channel. The transmitted information is reconstructed in the receiver end. Since only few samples are used here to reconstruct the original image, there may be the possibilities of degraded quality in reconstruction. In such cases image enhancement is carried out with traditional enhancement techniques after reconstruction. Such enhancements can now be done using the developing technique of compressed sensing by incorporating the various image processing techniques like edge detection, histogram, filtering etc. which increase the perceptual quality of the image. This paper proposes an embedded image enhancement technique inbuilt along with the compressed sensing process which provide better quality of reconstructed images. There is nearly 1dB increase in PSNR of the reconstructed image provided, the complexity remains unaltered.
机译：压缩感测（CS）是在信号处理中使用的技术，它通过找到不确定的线性系统的解来有效地获取和重建信号。在压缩感测中，数据在发送器端被压缩并转换为更少的测量值，并通过无线信道发送。所发送的信息在接收器端被重建。由于此处仅使用少量样本来重建原始图像，因此重建时可能会降低质量。在这种情况下，在重建后使用传统的增强技术进行图像增强。现在，可以通过结合各种图像处理技术（如边缘检测，直方图，滤波等）来使用压缩感测的开发技术来完成此类增强功能，这些技术可以提高图像的感知质量。本文提出了一种嵌入式图像增强技术，该技术与压缩传感过程一起内置，可以提供更好的重建图像质量。所提供的重建图像的PSNR增加了近1dB，复杂度保持不变。

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