Xi'an Jiaotong University City College, Xi'an, Shanxi 710068, China.
Comput Intell Neurosci. 2021 Nov 22;2021:8546987. doi: 10.1155/2021/8546987. eCollection 2021.
In digital media art, expressive force is an important art form of media. This paper studies digital images that have the same effect when applied to media art. The research object is media art images, and the application effect of the proposed algorithm is related to the media art images. The development of digital image technology has brought revolutionary changes to traditional media art expression techniques. In this paper, a partial-pixel interpolation technique based on convolutional neural network is proposed. Supervised training of convolutional neural networks requires predetermining the input and target output of the network, namely, integer image and fractional image in this paper. To solve the problem that the subpixel sample cannot be obtained, this paper first analyzes the imaging principle of digital image and proposes a subpixel sample generation algorithm based on Gaussian low-pass filter and polyphase sampling. From the perspective of rate distortion optimization, the purpose of pixel motion compensation is to improve the accuracy of interframe prediction. Therefore, this paper defines pixel motion compensation as an interframe regression problem, that is, the mapping process of the reference image integral pixel sample to the current image sample to be encoded. In this paper, a generalized partial-pixel interpolation model is proposed for bidirectional prediction. The partial-pixel interpolation of bidirectional prediction is regarded as a binary regression model; that is, the integral pixel reference block in two directions is mapped to the current block to be coded. It further studies how to apply the trained digital images to media art design more flexibly and efficiently.
在数字媒体艺术中，表现力是媒体的一种重要艺术形式。本文研究应用于媒体艺术时具有相同效果的数字图像。研究对象为媒体艺术图像，提出算法的应用效果与媒体艺术图像有关。数字图像技术的发展给传统媒体艺术表现手法带来了革命性的变化。本文提出了一种基于卷积神经网络的部分像素插值技术。卷积神经网络的监督训练需要预先确定网络的输入和目标输出，即本文中的整数图像和分数图像。为了解决亚像素样本无法获取的问题，本文首先分析数字图像的成像原理，提出了一种基于高斯低通滤波器和多相采样的亚像素样本生成算法。从率失真优化的角度来看，像素运动补偿的目的是提高帧间预测的准确性。因此，本文将像素运动补偿定义为帧间回归问题，即参考图像整像素样本到当前待编码图像样本的映射过程。本文针对双向预测提出了一种广义部分像素插值模型。双向预测的部分像素插值被视为二进制回归模型，即两个方向的整像素参考块被映射到要编码的当前块。它进一步研究了如何更灵活、更有效地将训练有素的数字图像应用于媒体艺术设计。
