Configurable implementation of parallel memory based real-time video downscaler
Microprocessors & Microsystems
A Simple Scaling Algorithm Based on Areas Pixels
ICIAR '08 Proceedings of the 5th international conference on Image Analysis and Recognition
Memory Efficient VLSI Architecture for QCIF to VGA Resolution Conversion
PSIVT '09 Proceedings of the 3rd Pacific Rim Symposium on Advances in Image and Video Technology
A General-Purpose FPGA-Based Reconfigurable Platform for Video and Image Processing
ISNN 2009 Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part III
VLSI implementation of an edge-oriented image scaling processor
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
A comprehensive study of visual cryptography
Transactions on data hiding and multimedia security V
New aspect ratio invariant visual secret sharing schemes using square block-wise operation
ICIAR'05 Proceedings of the Second international conference on Image Analysis and Recognition
A new image scaling algorithm based on the sampling theorem of papoulis
ICIAR'07 Proceedings of the 4th international conference on Image Analysis and Recognition
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We propose a new scaling algorithm, winscale, which performs the scale up/down transform using an area pixel model rather than a point pixel model. The proposed algorithm has low complexity: the algorithm uses a maximum of four pixels of an original image to calculate one pixel of a scaled image. Nevertheless, the algorithm has good characteristics such as fine-edge and changeable smoothness. We implemented a hardware design of winscale using an FPGA and displayed some test scenes in an liquid crystal display panel using a digital visual interface. The hardware cost and the image quality were compared with those of the conventional image scaling algorithms. It is proved that winscale has good scale property with low complexity. Winscale can be used in various digital display devices that need image scaling, especially in applications that require good image quality with low hardware cost.