0000000000331442
AUTHOR
Salvatore Curti
Real metrology by using depth map information
Usually in an image no real information about the scene’s depth (in terms of absolute distance) is available. In this paper, a method that extracts real depth measures is developed. This approach starts considering a region located in the center of the depth map. This region can be positioned, interactively, in any part of the depth map in order to measure the real distance of every object inside the scene. The histogram local maxima of this region are determined. Among these values the biggest, that represents the gray-level of the most considerable object, is chosen. This gray-level is used in an exponential mapping function that converts, using the input camera settings, the depth map gr…
Restoration of out-of-focus images based on circle of confusion estimate
In this paper a new method for a fast out-of-focus blur estimation and restoration is proposed. It is suitable for CFA (Color Filter Array) images acquired by typical CCD/CMOS sensor. The method is based on the analysis of a single image and consists of two steps: 1) out-of-focus blur estimation via Bayer pattern analysis; 2) image restoration. Blur estimation is based on a block-wise edge detection technique. This edge detection is carried out on the green pixels of the CFA sensor image also called Bayer pattern. Once the blur level has been estimated the image is restored through the application of a new inverse filtering technique. This algorithm gives sharp images reducing ringing and c…
Depth Map Generation by Image Classification
This paper presents a novel and fully automatic technique to estimate depth information from a single input image. The proposed method is based on a new image classification technique able to classify digital images (also in Bayer pattern format) as indoor, outdoor with geometric elements or outdoor without geometric elements. Using the information collected in the classification step a suitable depth map is estimated. The proposed technique is fully unsupervised and is able to generate depth map from a single view of the scene, requiring low computational resources.
Improved multi-resolution image fusion
This work describes an automatic technique able to fuse different images of the same scene, acquired at different settings, in order to obtain an enhanced single representation of the scene of interest by an improved picture fusion scheme. This allows the extending of the functionalities (depth of field, dynamic range) of medium and low cost digital cameras. When multi-scale decomposition is used on multi-focused images, magnification effects of the lens focusing system cause an incorrect estimation of all pixels in the final image. In our approach new techniques able to reduce these artifacts are introduced. The algorithm has been applied both on full RGB and on color filter array (CFA) im…
Automatic image enhancement by picture fusion
This paper describes an automatic technique able to fuse different images of the same scene, acquired with different camera settings, in order to obtain an enhanced single representation of the interested. This allows to extend the functionalities (depth of field, dynamic range) of medium and low cost digital cameras. When Multi-Scale Decomposition (MSD) is used on differently focused images, magnification and blurring effects of lens focusing systems often compromise the final image with unpleasant artifacts. In our approach new techniques able to reduce these artifacts are introduced. Even if the algorithm has been essentially designed to extend depth of field it can be also used on multi…