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FPGA implementation of a fast pipeline architecture for JND computation

机译:FPGA实现JND计算的快速管道架构

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Just Noticeable Distortion (JND) based on human visual system (HVS) is widely used in the transparent watermarking. But the computation of JND is very complex, which makes it difficult to embed it into integrated circuits. To solve this problem, Haar Wavelet based JND model is exploited in this paper. Furthermore, the fast pipeline architecture based on haar-wavelet for JND computation is developed. The architecture is modeled with hardware description language, and implemented on Altera EP2C35 FPGA device in order to evaluate the its performance. The hardware cost of JND core is 1460 Logic Cell combinations and 330 registers, which is significantly smaller than the Full Band JND based architecture. From the experiment results, the system goes on well with a 120MHz clock. Compared with the full band JND based architecture, ours achieves 75% time saving.
机译:仅基于人类视觉系统(HVS)的明显失真(JND)广泛用于透明水印中。 但是JND的计算非常复杂,这使得难以将其嵌入到集成电路中。 为了解决这个问题,本文利用了哈尔小波的JND模型。 此外,开发了基于HAAR-小波用于JND计算的快速流水线架构。 该架构采用硬件描述语言建模,并在Altera EP2C35 FPGA设备上实现,以评估其性能。 JND核心的硬件成本是1460个逻辑单元组合和330个寄存器,其显着小于基于频段JND的架构。 从实验结果中,系统与120MHz时钟相处。 与全频段基于JND的架构相比,我们的节省了75%。

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