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Restoration of color images by multichannel Kalman filtering

机译:通过多通道卡尔曼滤波恢复彩色图像

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A Kalman filter for optimal restoration of multichannel images is presented. This filter is derived using a multichannel semicausal image model that includes between-channel degradation. Both stationary and nonstationary image models are developed. This filter is implemented in the Fourier domain and computation is reduced from O( Lambda /sup 3/N/sup 3/M/sup 4/) to O( Lambda /sup 3/N/sup 3/M/sup 2/) for an M*M N-channel image with degradation length Lambda . Color (red, green, and blue (RGB)) images are used as examples of multichannel images, and restoration in the RGB and YIQ domains is investigated. Simulations are presented in which the effectiveness of this filter is tested for different types of degradation and different image model estimates.
机译:提出了一种用于多通道图像最佳恢复的卡尔曼滤波器。使用包含通道间降级的多通道半因果图像模型导出此滤波器。开发了固定和非固定图像模型。该滤波器在傅立叶域中实现,计算量从O(Lambda / sup 3 / N / sup 3 / M / sup 4 /)减少到O(Lambda / sup 3 / N / sup 3 / M / sup 2 /)对于具有退化长度Lambda的M * M N通道图像。彩色(红色,绿色和蓝色(RGB))图像用作多通道图像的示例,并研究了RGB和YIQ域中的恢复。给出了仿真,其中针对不同类型的退化和不同的图像模型估计测试了该滤波器的有效性。

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