Compressive Sensing, as an emerging technique in signal processing is reviewed in this paper together with its' common applications. As an alternative to the traditional signal sampling, Compressive Sensing allows a new acquisition strategy with significantly reduced number of samples needed for accurate signal reconstruction. The basic ideas and motivation behind this approach are provided in the theoretical part of the paper. The commonly used algorithms for missing data reconstruction are presented. The Compressive Sensing applications have gained significant attention leading to an intensive growth of signal processing possibilities. Hence, some of the existing practical applications assuming different types of signals in real-world scenarios are described and analyzed as well.

An algorithm for decomposition of highly multicomponent signals, with variable components energy, has been proposed. The algorithm combines the singular value decomposition with the suitable time-frequency analysis approach. The auto-correlation matrix is obtained by applying the inverse form of the cross-terms free time-frequency distribution. The decomposition of the time-frequency based auto-correlation matrix produces vectors that correspond to the individual signal components. The efficiency of the proposed algorithm has been tested on different signals.

Fresh garlic scape is popular for its unique tastes and special antibacterial effect. As a kind of seasonal vegetable, it has huge quality decay after harvesting, and usually by low temperature storage to approach the round-year supply. However, it lacks cold chain management directions and transparency, which depends heavily on the realtime information of the process environments and the quality of fresh garlic scapes.With the analyzed quality-related indicators, including temperature, relative humidity, gas composition and vibration, a multi-sensors information acquisition system based on wireless sensor network was designed and developed. Then, the process of the fresh garlic scapes supply were systematically analyzed and identified, and the proposed system was also evaluated using the monitored data in current practices.Results show that the transportation and cold storage occupies an important position in the typical garlic scapes supply process, which has continuous influences on the quality preservation. The developed system functions well, and the wireless multisensors nodes can real-time monitor environmental information with high data reliability. The data evaluation also demonstrates the association of the monitored quality-related data with the supply process stage. Meanwhile, it is the visualization of the quality-related data that enhance the real-time sensing of the quality in storage, the transparency of the supply process and the cold chain management level. Furthermore, the system should be further enhanced with the better data quality acquired by the nodes for better quality sensing and management of the fresh garlic scapes supply process. Practical ApplicationsSignificant benefits of this work are anticipated on the postharvest and preservation of garlic scapes to the market and reduction of its losses in the postharvest chain.

-Although the protection of ownership and the prevention of unauthorized manipulation of digital images becomes an important concern, there is also a big issue of image source origin authentication. This paper proposes a procedure for the identification of the image source and content by using the Public Key Cryptography Signature (PKCS). The procedure is based on the PKCS watermarking of the images captured with numerous automatic observing cameras in the Trap View cloud system. Watermark is created based on 32-bit PKCS serial number and embedded into the captured image. Watermark detection on the receiver side extracts the serial number and indicates the camera which captured the image by comparing the original and the extracted serial numbers. The watermarking procedure is designed to provide robustness to image optimization based on the Compressive Sensing approach. Also, the procedure is tested under various attacks and shows successful identification of ownership.

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