Image restoration consists in recovering a high quality image estimate based only on observations. This is considered an ill-posed inverse problem, which implies non-unique unstable solutions. Regularization methods allow the introduction of constraints in such problems and assure a stable and unique solution. One of these methods is Total Variation, which has been broadly applied in signal processing tasks such as image denoising, image deconvolution, and image inpainting for multiple noise scenarios. Total Variation features a regularization parameter which defines the solution regularization impact, a crucial step towards its high quality level. Therefore, an optimal selection of the regularization parameter is required. Furthermore, while the classic Total Variation applies its constraint to the entire image, there are multiple scenarios in which this approach is not the most adequat...

Image restoration consists in recovering a high quality image estimate based only on observations. This is considered an ill-posed inverse problem, which implies non-unique unstable solutions. Regularization methods allow the introduction of constraints in such problems and assure a stable and unique solution. One of these methods is Total Variation, which has been broadly applied in signal processing tasks such as image denoising, image deconvolution, and image inpainting for multiple noise scenarios. Total Variation features a regularization parameter which defines the solution regularization impact, a crucial step towards its high quality level. Therefore, an optimal selection of the regularization parameter is required. Furthermore, while the classic Total Variation applies its constraint to the entire image, there are multiple scenarios in which this approach is not the most adequat...

Este documento muestra el diseño de un sistema de registro de imágenes orientado a la agricultura de precisión en la producción de papa. Dicho sistema tiene como propósito la generación de mosaicos a partir de conjuntos de imágenes multiespectrales de campos de cultivo tomadas a cierto nivel sobre la superficie terrestre y bajo diferentes puntos de vista. La creación de esta imagen global busca obtener información correctamente localizada de la energía absorbida por la vegetación, de tal manera que se pueda definir con precisión su nivel nutricional en regiones e instantes determinados.

Este documento muestra el diseño de un sistema de registro de imágenes orientado a la agricultura de precisión en la producción de papa. Dicho sistema tiene como propósito la generación de mosaicos a partir de conjuntos de imágenes multiespectrales de campos de cultivo tomadas a cierto nivel sobre la superficie terrestre y bajo diferentes puntos de vista. La creación de esta imagen global busca obtener información correctamente localizada de la energía absorbida por la vegetación, de tal manera que se pueda definir con precisión su nivel nutricional en regiones e instantes determinados.