通过图像处理降低手机间可见光通信的模糊，提升数据接收效率。
An Image Processing Based Blur Reduction Technique in Smartphone-to-Smartphone Visible Light Communication System
- 将RGB转为灰度图，再增强对比度、缩放、二值化以减少模糊。
- 在不同距离、角度和光照下，接收端数据恢复率提升至96%。
- 适合做手机间可见光通信系统优化，尤其在复杂环境中有优势。
本文提出一种针对手机到手机可见光通信（S2SVLC）的模糊抑制技术，旨在避免重复扫描发送数据，并减少接收端丢弃的数据量。该图像处理方法包括将红绿蓝（RGB）图像转换为灰度图，进行对比度增强、缩放和二值化操作，从而降低图像模糊程度。实验在不同距离、旋转、倾斜及环境光照（如环境光与无光条件）下进行，使用美国信息交换标准代码（ASCII）和快速响应码（QR码）作为传输编码。结果表明，所提方法在各种条件下均能将接收端数据恢复效率提升至96%。
原文摘要 · Abstract (English)
In this paper, we present a blur reduction technique for smartphone-to-smartphone visible light communications (S2SVLC). The key technique it to avoid the repeated scanning of the transmitted data and to lower the amount of data discarded at the receiver end of the S2SVLC system. This image processing method will improve the system recognition efficiency and data rate. The proposed method includes converting the red-green-blue (RGB) image into grayscale, applying contrast enhancement, scaling and binarizing the image to reduce the blur levels in the image. The experiment includes practical data acquisition and further processing and estimation in MATLAB. The experiment is carried out in different conditions like distance, rotation, and tilt also considering different surrounding illuminations like ambient light and no light conditions to estimate the blur levels in S2SVLC. In this experimental investigation two types of coding, American Standard code for information interchange (ASCII), and quick response (QR) code are used for data transmission in S2SVLC. The obtained results indicate that, the proposed technique is proven to improve the recovery efficiency to 96% in the receiver end at different conditions.
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