In this paper, the theory and the design of a new class of orthogonal transforms are presented. The novel transform is derived from a correlation matrix in which an arbitrary orthonormal system is embedded. By embedding an orthonormal system designed empirically, we obtain the transform that can not only represent intuitive features but also possess statistical property like the KLT. Our main motivation is the application in block-based adaptive transforms coding. We show a design example of the transform, which adapts orientational features such as edges and lines. Using this transform, we perform orientation adaptive coding. In experimental results, it is shown that image coding using the transform is eective in rate-distortion criterion and subjective quality.