英语翻译For each test image from validation set,a quantitative measure\2p,called patch to patch mean error (henceforth P2PME),is appliedto evaluate the reconstruction quality.By averaging all distancesbetween reconstructed and true high-resolutio

英语翻译For each test image from validation set,a quantitative measure\2p,called patch to patch mean error (henceforth P2PME),is appliedto evaluate the reconstruction quality.By averaging all distancesbetween reconstructed and true high-resolutio
英语翻译
For each test image from validation set,a quantitative measure
\2p,called patch to patch mean error (henceforth P2PME),is applied
to evaluate the reconstruction quality.By averaging all distances
between reconstructed and true high-resolution patches,the
P2PME \2p is formulated as follows:
where bYi denotes the ith patch recovered and Yi its corresponding
ground truth.bYiðjÞ and YiðjÞ are the jth points in the respective
patches with S \2 S points.P denotes the total number of patches.
An advantage using Eq.(6) is that \2p works on a patch scale rather
than pixel scale,so that it can reflect more exactly about the recovery
quality of patch based super-resolution,before the overlapping
patches are averaged and smoothed and finally turned into dependent
pixels.
The \2p values for each test image taken from the first six validation
images are shown in Fig.3a.The denotations of the legend are
as follows:1.First-order gradient; 2.second-order gradient; 3.
norm luminance; al:Weighting factor a between combination of
1 and 3.And combination of such notes means concatenation of
the corresponding features.For example,13 means concatenation
of first-order gradient and norm luminance as feature vector.
As Fig.3 demonstrates,features concerning the combination of
first-order gradients and norm luminance with and without a (denoted
by 13 and 13al) have relatively lower P2PME than any other
single feature and combination for the first six validation images
when these images are used for test.When a ¼ 4,especially,feature
13al achieves best P2PME,significantly lower than most of
the other features.First-order gradient feature provides acceptable
errors as well,but we will show that its visual results are of blurry
quality (see Fig.7).The variances of patch to patch errors of the
13al are also lowest,suggesting the most stable performance for
the reconstruction.

英语翻译For each test image from validation set,a quantitative measure\2p,called patch to patch mean error (henceforth P2PME),is appliedto evaluate the reconstruction quality.By averaging all distancesbetween reconstructed and true high-resolutio
For each test image from validation set,a quantitative measure p,called patch to patch mean error (henceforth P2PME),is applied to evaluate the reconstruction quality.
对于从确认的那批图象中选出的测试图象,我们用一个量化的测量标准 p,叫做碎片之间的平均误差（后文简称P2PME）,来评价其重构质量.
By averaging all distances between reconstructed and true high-resolution patches,the P2PME p is formulated as follows:
通过将重构和真正高分辨图象碎片之间的差距平均化,P2PME p用以下公式表示：
where bYi denotes the ith patch recovered and Yi its corresponding ground truth.bYiðjÞ and YiðjÞ are the jth points in the respective patches with S S points.P denotes the total number of patches.
其中bYi表示所包含的ith碎片,Yi表示其相应的真实部分.bYiðjÞ 和 YiðjÞ是带S S点分数的各自碎片的jth 分数.P表示碎片总数.
An advantage using Eq.(6) is that p works on a patch scale rather than pixel scale,so that it can reflect more exactly about the recovery quality of patch based super-resolution,before the overlapping patches are averaged and smoothed and finally turned into dependent pixels.
使用Eq.(6)的优势在于：p用碎片衡量胜于用象素衡量,因此它能更加正确地反映超分辨图象所覆盖的碎片数量,即在重合之前碎片经过平均化和平滑处理并且最终变成相互关联的象素.
The p values for each test image taken from the first six validation images are shown in Fig.3a.The denotations of the legend are as follows:
图示3a显示了从最初6个确认的图象中获取的每个测试图象的 p值.该图例示意如下：
1.First-order gradient; 2.second-order gradient; 3.norm luminance; al:Weighting factor a between combination of 1 and 3.And combination of such notes means concatenation of the corresponding features.For example,13 means concatenation of first-order gradient and norm luminance as feature vector.
1、第一顺序梯度；2、第二顺序梯度；3、常规亮度；al:1和3之间组合的权重因数.并且这些注解的组合意味着相应特征的组合.比如：13意味着第一顺序梯度和常规亮度在特征向量上的组合.
As Fig.3 demonstrates,features concerning the combination of first-order gradients and norm luminance with and without a (denoted by 13 and 13al) have relatively lower P2PME than any other single feature and combination for the first six validation images when these images are used for test.
如图3所示,和任何其他单一特征、以及从要做测试的图象中最初确认的6个图象的组合相比,关于第一顺序梯度和常规亮度组合的、带有和不带有a（以13和13a表示）的特征,具有相对较底的P2PME.
When a ¼ 4,especially,feature 13al achieves best P2PME,significantly lower than most of the other features.
特别是当a ¼ 4时,特征13al达到最佳的P2PME,非常醒目地低于其他大多数特征.
First-order gradient feature provides acceptable errors as well,but we will show that its visual results are of blurry quality (see Fig.7).
第一顺序梯度特征也提供了可接受的误差,但我们将展示其视觉效果是属于模糊性质的（见图示7）
The variances of patch to patch errors of the 13al are also lowest,suggesting the most stable performance for the reconstruction.
13al的碎片之间的误差变异也是最小的,寓示其图象重构性能最为稳定.