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. In these last years have been calculated several general algorithms to process the images acquired by mobile devices. Nevertheless, they don't always work at their full effectiveness due the numerous constraints and external issues. The latest generation smartphones, pushed by higher user expectations, have increasingly performing camera functions, in particular way, about the always increasing resolution, with a large number of pixels to process or two cameras for stereo view. Considering that pixels in an image sensor synthetizes the number of incoming photons, taking a photograph with a digital camera means to applying a low-pass filter to a scene where the tiny textures, such as characters that measure a few pixels, are observed blurry. This happens when using digital zoom or when the visibility is compromised or during the night artificial lights. For all these reasons the conventional image converter resolution algorithms (as bilinear interpolation algorithm) don’t work with the high-frequency information of a scene once lost. All these aspects are more relevant if we are taking photos to carry out a 3D scenario. Indeed, the 3D model will have an higher geometric accuracy if the image resolution will be higher. Super-Resolution algorithms (SRa) are classified into two categories: (1) approaches that reconstruct a high-resolution image from itself and (2) approaches that register multiple low-resolution images to interpolate sub-pixel information. In this paper we verify the geometric accuracy of a 3D model, when using the Morpho Super-Resolution™ algorithm, also in critical condition. This algorithm doesn’t require pixel shift, indeed, some cameras have a functionality named pixel shift, which captures multiple images while shifting the image sensor.

the international archives of the photogrammetry, remote sensing and spatial information sciences/international archives of the photogrammetry, remote sensing and spatial information sciences

SUPER-RESOLUTION IMAGES ON MOBILE SMARTPHONE AIMED AT 3D MODELING