Polyphase interpretation of empirical image interpolation

• Main Authors: Ni, Karl S. (Contributor), Nguyen, Truong Q. (Author)
• Other Authors: Lincoln Laboratory (Contributor)
• Format: Article
• Language: English
• Published: Institute of Electrical and Electronics Engineers, 2010-12-02T20:00:26Z.
• Subjects: Article
• Online Access: Get fulltext

 We observe several characteristics of empirical image interpolating algorithms and contribute four novel concepts and claims. First, we interpret well-known classification-based filtering algorithms in terms of their polyphase components. We examine the underlying principles behind the various fixed-scale linear interpolating kernels. Second, we conceptually extend the properties of the multiple filters to two dimensions to analyze frequency domain characteristics common to all empirically-designed interpolating filters. Third, we propose a general linear filter for image interpolation, which uses a universal magnitude response and zero-phase. Finally, the proposed filter is further generalized to support arbitrary scaling factors. We claim that at any scaling factor, the proposed algorithm yields low-complexity at a minimal loss of high image-quality with the ability to interpolate diverse image content.