期刊文献+

一种改进的低成本自适应双三次插值算法及VLSI实现 被引量:17

An Improved Low-cost Adaptive Bicubic Interpolation Arithmetic and VLSI Implementation
下载PDF
导出
摘要 提出了一种新型图像缩放算法,由自适应锐化滤波器和双三次插值组成.锐化滤波器减轻了双三次插值产生的模糊效应,自适应技术进一步提升了图像缩放质量.为了减少运算量,提出前置滤波和后置滤波技术.与其他几种算法相比较,本文的算法在主观和客观评价方面都明显胜出.为了实现实时低成本设计,提出了一种该算法的流水线超大规模集成电路(Very large scale integration,VLSI)架构.在现场可编程逻辑器件(Field-programmable gate array,FPGA)上实现,占用695个逻辑单元(Logic elements,LEs),时钟频率达到165MHz,减少了36.8%逻辑单元,图像质量平均峰值信噪比(Peak signal-to-noise ratio,PSNR)提升了1.5dB. A novel scaling algorithm is proposed which consists of a bicubic interpolation and an adaptive sharpening filter. The proposed sharpening filter is added to mitigate the blurring effects existing in bicubic interpolation methods. We also verify the scaling quality by taking into account the adaptive technique. Furthermore, we present both the procedures of filtering before and after interpolation in order to reduce the overall computing time. Compared with the previous reported techniques, our method performs better in terms of both quantitative evaluation and visual quality. To achieve the goal of real time and low cost, we describe a pipelined VLSI architecture for the implementation of the algorithm. The very large scale integration (VLSI) architecture of our image scaling processor contains 695 logic elements (LEs) and yields a processing rate of about 165 MHz by using field-programmable gate array (FPGA) technology. Our proposed architecture reduces the amount of gates by 36.8 % while achieves an average peak signal-to-noise ratio (PSNR) increase of 1.5 dB in image quality.
出处 《自动化学报》 EI CSCD 北大核心 2013年第4期407-417,共11页 Acta Automatica Sinica
基金 广东省战略新兴产业关键技术产业化专项(2011168014 2011912004) 广东省省部产学研重点科技项目(2011A090200037)资助~~
关键词 双三次插值 图像缩放 拉普拉斯变换 自适应 超大规模集成电路 现场可编程逻辑器件 Bicubic interpolation image scaling Laplacian transform adaptive very large scale integration (VLSI) field-programmable gate array (FPGA)
  • 相关文献

参考文献30

  • 1Chen S L, Huang H Y, Luo C H. A low-cost high-quality adaptive scalar for real-time multimedia applications. IEEE Transactions on Circuits and Systems for Video Techology, 2011, 21(11): 1600--1611.
  • 2Hwang I, Kang B, Gerard J. High-resolution image scaler using interpolation filter for multimedia video applications. IEEE Transactions on Consumer Electronics, 1997, 43(3): 813-818.
  • 3Doswald D, Hafliger J, Blessing P, Felber N, Niederer P, Fichtner W. A 30-frames/s megapixel real-time CMOS im- age processor. IEEE Journal of Solid-State Circuits, 2000, 35(11): 1732-1743.
  • 4Lehmann T M, Gonner C, Spitzer K. Addendum: B-spline interpolation in medical image processing. IEEE Trnnsnc- tions on Medical Imaging, 2001, 20(7): 660--665.
  • 5Battiato S, Gallo G, Stanco F. A locally adaptive zooming algorithm for digital images. Image and Vision Computing, 2002, 20(11): 805-812.
  • 6Chen M J, Huang C H, Lee W L. A fast edge-oriented algo- rithm for image interpolation. Image and Vision Computing, 2005, 23(9): 791-798.
  • 7Shi J Z, Reichenbach S E. Image interpolation by two- dimensional parametric cubic convolution. IEEE Transac- tions on Image Processing, 2006, 15(7): 1857--1870.
  • 8Chen J L, Chang J Y, Shieh K L. 2-D discrete signal inter- polation and its image resampling application using fuzzy rule-based inference, Fuzzy Sets and Systems, 2000, 114(2): 225-238.
  • 9Blu T, Thevenaz P, Unser M. Linear interpolation revital- ized. IEEE Transactions on Image Processing, 2004, 13(5): 710-719.
  • 10Meijering E H W, Zuiderveld K J, Viergever M A. Image reconstruction by convolution with symmetrical piecewise nth-order polynomial kernels. IEEE Transactions on Image Processings, 1999, 8(2): 192-201.

同被引文献148

引证文献17

二级引证文献108

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部