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A Novel Image Mosaicking Technique for Enlarging the Field of View of Images Transmitted over Wireless Image Sensor Networks

机译:一种新的图像拼接技术,用于扩大通过无线图像传感器网络传输的图像的视场

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Existing image mosaicking algorithms generate a complete scene that incorporates a number of images captured by several cameras. The traditional image mosaicking approaches cannot be applied directly to the emerging Wireless Image Sensor Networks (WISNs), since the low performance of image transmission over wireless sensor networks causes a noticeable delay before an entire image is received by a control center node. In this work, we propose a Progressive Image Mosaicking Algorithm (PIMA) based on the multi-scan feature of Progressive JPEG (P-JPEG). The originality of PIMA is based essentially on how it successfully performs mosaicking by using incremental image quality, as opposed to traditional methods that require complete data from all images. PIMA builds mosaics of images that are decoded from P-JPEG scans at three levels of quality, and delivers an approximate view of the scene in a short time while the reception of further image data is still in progress. Thereafter,rnit updates the image registration on two other refined levels to gradually enhance the display quality. We also propose the concept of Richer Information and Likeliest (RIL) block pair, which is a variation of the Sum of Absolute Difference (SAD). RIL can improve significantly the accuracy of image registration. We have conducted an extensive set of experiments and evaluated our proposed schemes against selected existing approaches. Our performance results indicate that PIMA decreases the delay before the first display of the scene, while preserving equivalent performance and image quality when compared to existing patch-based image mosaicking algorithms.
机译:现有的图像镶嵌算法会生成一个完整的场景,其中包含了多个由摄像机捕获的图像。传统的图像拼接方法无法直接应用于新兴的无线图像传感器网络(WISN),因为无线传感器网络上图像传输的低性能会导致控制中心节点接收到整个图像之前的明显延迟。在这项工作中,我们基于渐进JPEG(P-JPEG)的多重扫描功能,提出了渐进式图像拼接算法(PIMA)。 PIMA的独创性主要取决于它如何通过使用增量图像质量成功执行镶嵌,而不是传统方法要求从所有图像获得完整数据的传统方法。 PIMA建立从P-JPEG扫描解码的图像的三种质量的马赛克,并在仍在接收其他图像数据的同时,在短时间内提供场景的大致视图。此后,rnit在其他两个精细级别上更新图像配准,以逐渐提高显示质量。我们还提出了“更丰富的信息和最可能的(RIL)块对”的概念,它是绝对差总和(SAD)的变体。 RIL可以显着提高图像配准的准确性。我们进行了一系列广泛的实验,并针对某些现有方法对我们提出的方案进行了评估。我们的性能结果表明,与现有的基于补丁的图像镶嵌算法相比,PIMA减少了首次显示场景之前的延迟,同时保留了等效的性能和图像质量。

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