图像处理任务中广泛应用中值滤波器来平滑图像和消除幅度极大或极小的噪声,并且可以保持图像的边缘特性,不会使图像产生明显模糊。提出一种改进的空间域量子彩色图像中值滤波算法,并且在IBM Q(international business machines quantum...图像处理任务中广泛应用中值滤波器来平滑图像和消除幅度极大或极小的噪声,并且可以保持图像的边缘特性,不会使图像产生明显模糊。提出一种改进的空间域量子彩色图像中值滤波算法,并且在IBM Q(international business machines quantum)平台上进行仿真。该算法将量子彩色图像进行存储,利用量子比较器模块、量子控制交换器模块、中值计算模块和阈值模块设计量子彩色图像中值滤波的量子线路。相较于已有的量子彩色图像中值滤波算法,在进行中值滤波之前加入了阈值进行噪声判断,该算法滤波效果更好,同时时间复杂度也更低。展开更多
A new depth resampling for multi-view coding is proposed in this paper.At first,the depth video is downsampled by median filtering before encoding.After decoding,the classified edges,including credible edge and probab...A new depth resampling for multi-view coding is proposed in this paper.At first,the depth video is downsampled by median filtering before encoding.After decoding,the classified edges,including credible edge and probable edge from the aligned texture image and the depth image,are interpolated by the selected diagonal pair,whose intensity difference is the minimum among four diagonal pairs around edge pixel.According to different category of edge,the intensity difference is measured by either real depth or percentage depth without any parameter setting.Finally,the resampled depth video and the decoded full-resolution texture video are synthesized into virtual views for the performance evaluation.Experiments on the platform of multi-view high efficiency video coding(HEVC) demonstrate that the proposed method is superior to the contrastive methods in terms of visual quality and rate distortion(RD) performance.展开更多
文摘图像处理任务中广泛应用中值滤波器来平滑图像和消除幅度极大或极小的噪声,并且可以保持图像的边缘特性,不会使图像产生明显模糊。提出一种改进的空间域量子彩色图像中值滤波算法,并且在IBM Q(international business machines quantum)平台上进行仿真。该算法将量子彩色图像进行存储,利用量子比较器模块、量子控制交换器模块、中值计算模块和阈值模块设计量子彩色图像中值滤波的量子线路。相较于已有的量子彩色图像中值滤波算法,在进行中值滤波之前加入了阈值进行噪声判断,该算法滤波效果更好,同时时间复杂度也更低。
基金supported by the National Natural Science Foundation of China(Nos.61401132 and 61372157)the Zhejiang Provincial Natural Science Foundation of China(No.LY12F01007)
文摘A new depth resampling for multi-view coding is proposed in this paper.At first,the depth video is downsampled by median filtering before encoding.After decoding,the classified edges,including credible edge and probable edge from the aligned texture image and the depth image,are interpolated by the selected diagonal pair,whose intensity difference is the minimum among four diagonal pairs around edge pixel.According to different category of edge,the intensity difference is measured by either real depth or percentage depth without any parameter setting.Finally,the resampled depth video and the decoded full-resolution texture video are synthesized into virtual views for the performance evaluation.Experiments on the platform of multi-view high efficiency video coding(HEVC) demonstrate that the proposed method is superior to the contrastive methods in terms of visual quality and rate distortion(RD) performance.
