In recent years, the computational power of handheld devices has increased rapidly to the point of parity with computers of only a generation ago. The multiple tools integrated into these devices and the progressive expansion of cloud storage have created a need for novel compressing techniques for both storage and transmission. In this work, a novel L1 principal component analysis (PCA) informed K-means approach is proposed. This new technique seeks to preserve the color definition of images through the application of K-means clustering algorithms. Assessment of the efficacy is carried out utilizing the structural similarity index (SSIM).
Free space optical (FSO) communication systems can be used to transmit data at a high data rate while being immune to noise that typical communication systems are susceptible to. Current radio frequency (RF) trans- mission systems are flooding the usable spectrum, causing it to become overcrowded and inconvenient to use. This results in more noise and potentially a lower bandwidth based on the part of the spectrum a given RF system is able to operate in. The free space optical transceiver (FSO-TRx) system proposed in this paper helps solve these issues with a modular and scalable design.
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