In this work we explored class separability in feature spaces built on extended representations of pixel planes (EPP) produced using scale pyramid, subband pyramid, and image transforms. The image transforms included Chebyshev, Fourier, wavelets, gradient, and Laplacian; we also utilized transform combinations, including Fourier, Chebyshev, and wavelets of the gradient transform, as well as Fourier of the Laplacian transform. We demonstrate that all three types of EPP promote class separation. We also explored the effect of EPP on suboptimal feature libraries, using only textural features in one case and only Haralick features in another. The effect of EPP was especially clear for these suboptimal libraries, where the transform-based representations were found to increase separability to a greater extent than scale or subband pyramids. EPP can be particularly useful in new applications where optimal features have not yet been developed.

中文翻译：

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使用扩展像素平面提高类可分离性：一项比较研究。

在这项工作中，我们探索了基于使用比例金字塔、子带金字塔和图像变换生成的像素平面 (EPP) 扩展表示的特征空间中的类可分离性。图像变换包括切比雪夫、傅立叶、小波、梯度和拉普拉斯；我们还利用了变换组合，包括梯度变换的傅里叶、切比雪夫和小波，以及拉普拉斯变换的傅里叶。我们证明了所有三种类型的 EPP 都促进了类分离。我们还探讨了 EPP 对次优特征库的影响，在一种情况下仅使用纹理特征，而在另一种情况下仅使用 Haralick 特征。EPP 的效果对于这些次优库尤其明显，其中发现基于变换的表示比尺度或子带金字塔在更大程度上增加了可分离性。