It is calculated as half of the value of the sampling rate.Passing this level causes aliasing distortion, or foldover.
它的计算方法是将采样率除以二,超过这个值将会导致折叠失真,或称折叠。
It is calculated as half of the value of the sampling rate.Passing this level causes aliasing distortion, or foldover.
它的计算方法是将采样率除以二,超过这个值将会导致折叠失真,或称折叠。
Our approach is based on a gradient domain technique that preserves important local perceptual cues while avoiding traditional problems such as aliasing, ghosting and haloing.
我们的方法是一种基于梯度方法的技术,保存了重要的局部视觉暗示并避免了传统的混淆现象,如鬼影和光晕的问题。
声明:以上例句、词性分类均由互联网资生成,部分未经过人工审核,其表达内容亦不代表本软件的观点;若发现问题,欢迎向我们指正。
It is calculated as half of the value of the sampling rate.Passing this level causes aliasing distortion, or foldover.
它计算方法是将采样率除以二,超过这个数值将会导致折叠失真,或称折叠。
Our approach is based on a gradient domain technique that preserves important local perceptual cues while avoiding traditional problems such as aliasing, ghosting and haloing.
我们方法是一种
度
方法
术,保存了重要
局部视觉暗示并避免了传统
混淆现象,如鬼影和光晕
问题。
声明:以上例句、词性分类均由互联网资源自动生成,部分未经过人工审核,其表达内容亦不代表本软件观点;若发现问题,欢迎向我们指正。
It is calculated as half of the value of the sampling rate.Passing this level causes aliasing distortion, or foldover.
计算方法是将采样率除以二,超过这个数值将会导致折叠失真,或称折叠。
Our approach is based on a gradient domain technique that preserves important local perceptual cues while avoiding traditional problems such as aliasing, ghosting and haloing.
我们方法是一种基于梯度
方法
技术,保存了重要
局部视觉暗示并避免了传统
混淆现象,如鬼影和光晕
问题。
声明:以上例、词
分类均由互联网资源自动生成,部分未经过人工审核,其表达内容亦不代表本软件
观点;若发现问题,欢迎向我们指正。
It is calculated as half of the value of the sampling rate.Passing this level causes aliasing distortion, or foldover.
它的计算方法是将采样率除以二,超过这个数值将会导致折叠,
称折叠。
Our approach is based on a gradient domain technique that preserves important local perceptual cues while avoiding traditional problems such as aliasing, ghosting and haloing.
我们的方法是一种基于梯度方法的技术,保存了重要的局部视觉
避免了传统的混淆现象,如鬼影和光晕的问题。
声明:以上例句、词性分类均由互联网资源自动生成,部分未经过人工审核,其表达内容亦不代表本软件的观点;若发现问题,欢迎向我们指正。
It is calculated as half of the value of the sampling rate.Passing this level causes aliasing distortion, or foldover.
它的计算方法是将采样率除以二,超过这个数值将会导致折叠失真,或称折叠。
Our approach is based on a gradient domain technique that preserves important local perceptual cues while avoiding traditional problems such as aliasing, ghosting and haloing.
我们的方法是一种基于梯度方法的技术,保存了重要的局部视觉暗示并避免了传统的混淆现象,如鬼影和光晕的问题。
声明:以上例句、词性类均由互联网资源自动生成,部
过人工审核,其表达内容亦不代表本软件的观点;若发现问题,欢迎向我们指正。
It is calculated as half of the value of the sampling rate.Passing this level causes aliasing distortion, or foldover.
它计算方法是
率除以二,超过这个数值
会导致折叠失真,或称折叠。
Our approach is based on a gradient domain technique that preserves important local perceptual cues while avoiding traditional problems such as aliasing, ghosting and haloing.
我们方法是一种基于梯度
方法
技术,保存了重要
局部视觉暗示并避免了传统
混淆现象,如鬼影和光晕
。
声明:以上例句、词性分类均由互联网资源自动生成,部分未经过人工审核,其表达内容亦不代表本软件观点;若发现
,欢迎向我们指正。
It is calculated as half of the value of the sampling rate.Passing this level causes aliasing distortion, or foldover.
它的计算方法是将采样率除以二,超过这个数值将会导致失真,或
。
Our approach is based on a gradient domain technique that preserves important local perceptual cues while avoiding traditional problems such as aliasing, ghosting and haloing.
我们的方法是一种基于梯度方法的技术,保存了重要的局
暗示并避免了传统的混淆现象,如鬼影和光晕的问题。
声明:以上例句、词性分类均由互联网资源自动生成,分未经过人工审核,其表达内容亦不代表本软件的观点;若发现问题,欢迎向我们指正。
It is calculated as half of the value of the sampling rate.Passing this level causes aliasing distortion, or foldover.
它的计算方法是将采样率除以二,超过这个数值将会导致叠失真,
叠。
Our approach is based on a gradient domain technique that preserves important local perceptual cues while avoiding traditional problems such as aliasing, ghosting and haloing.
我们的方法是一种基于梯度方法的技术,保存了重要的局部
示并避免了传统的混淆现象,如鬼影和光晕的问题。
声明:以上例句、词性分类均由互联网资源自动生成,部分未经过人工审核,其表达内容亦不代表本软件的观点;若发现问题,欢迎向我们指正。
It is calculated as half of the value of the sampling rate.Passing this level causes aliasing distortion, or foldover.
它的计算方法采样率除以二,超过这个数值
会导致折叠失真,或称折叠。
Our approach is based on a gradient domain technique that preserves important local perceptual cues while avoiding traditional problems such as aliasing, ghosting and haloing.
我们的方法一种基于梯度
方法的技术,保存了重要的局部视觉暗示并避免了传统的混淆现象,如鬼影和光晕的问
。
:以上例句、词性分类均由互联网资源自动生成,部分未经过人工审核,其表达内容亦不代表本软件的观点;若发现问
,欢迎向我们指正。