Giuliana Ramella

Italian National Research Council | CNR · Institute for Applied Mathematics "Mauro Picone" IAC

Spatial color algorithms (SCAs) are algorithms grounded in the retinex theory of color sensation that, mimicking the human visual system, perform image enhancement based on the spatial arrangement of the scene. Despite their established role in image enhancement, their potential as dequantizers has never been investigated. Here, we aim to assess th...

Image scaling methods allow us to obtain a given image at a different, higher (upscaling) or lower (downscaling), resolution to preserve as much as possible the original content and the quality of the image. In this paper, we focus on interpolation methods for scaling three-dimensional grayscale images. Within a unified framework, we introduce two...

Image resizing (IR) has a crucial role in remote sensing (RS), since an image’s level of detail depends on the spatial resolution of the acquisition sensor; its design limitations; and other factors such as (a) the weather conditions, (b) the lighting, and (c) the distance between the satellite platform and the ground targets. In this paper, we ass...

We present a new image scaling method both for downscaling and upscaling, running with any scale factor or desired size. The resized image is achieved by sampling a bivariate polynomial which globally interpolates the data at the new scale. The method’s particularities lay in both the sampling model and the interpolation polynomial we use. Rather t...

Image resizing is a basic tool in image processing, and in literature, we have many methods based on different approaches, which are often specialized in only upscaling or downscaling. In this paper, independently of the (reduced or enlarged) size we aim to get, we approach the problem at a continuous scale where the underlying function representin...

Skin lesion segmentation is one of the crucial steps for an efficient non-invasive computer-aided early diagnosis of melanoma. This paper investigates how to use colour information, besides saliency, for determining the pigmented lesion region automatically. Unlike most existing segmentation methods using only the saliency to discriminate against t...

We present a new image scaling method both for downscaling and upscaling, running with any scale factor or desired size. It is based on the sampling of an approximating bivariate polynomial, which globally interpolates the data and is defined by a filter of de la Vall\'ee Poussin type whose action ray is suitable regulated to improve the approximat...

Image resizing is a basic tool in image processing and in literature we have many methods, based on different approaches, which are often specialized in only upscaling or downscaling. In this paper, independently of the (reduced or enhanced) size we aim to get, we approach the problem at a continuous scale where the underlying continuous image is g...

The visual quality evaluation is one of the fundamental challenging problems in image processing. It plays a central role in the shaping, implementation, optimization, and testing of many methods. The existing image quality assessment methods centered mainly on images altered by common distortions while paying little attention to the distortion int...

In a computer-aided system for skin cancer diagnosis, hair removal is one of the main challenges to face before applying a process of automatic skin lesion segmentation and classification. In this paper, we propose a straightforward method to detect and remove hair from dermoscopic images. Preliminarily, the regions to consider as candidate hair re...

Skin lesion segmentation is one of the crucial steps for an efficient non-invasive computer-aided early diagnosis of melanoma. In this paper, we investigate how saliency and color information can be usefully employed to determine the lesion region. Unlike most existing saliency-based methods, to discriminate against the skin lesion from the surroun...

Visual quality evaluation is one of the challenging basic problems in image processing. It also plays a central role in the shaping, implementation, optimization, and testing of many methods. The existing image quality assessment methods focused on images corrupted by common degradation types while little attention was paid to color quantization. T...

In this paper, an adaptive method for copy-move forgery detection and localization in digital images is proposed. The method employs wavelet transform with non constant Q factor and characterizes image pixels through the multiscale behavior of corresponding wavelet coefficients. The detection of forged regions is then performed by considering simil...

The paper presents a method for color quantization (CQ) which uses visual contrast for determining an image-dependent color palette. The proposed method selects image regions in a hierarchical way, according to the visual importance of their colors with respect to the whole image. The method is automatic, image dependent and requires a moderate com...

The paper presents a novel method for color quantization (CQ) of dermoscopic images. The proposed method consists of an iterative procedure that selects image regions in a hierarchical way, according to the visual importance of their colors. Each region provides a color for the palette which is used for quantization. The method is automatic, image...

The paper presents a novel method for color quantization (CQ) of dermoscopic images. The proposed method consists of an iterative procedure that selects image regions in a hierarchical way, according to the visual importance of their colors. Each region provides a color for the palette which is used for quantization. The method is automatic, image...

A new color quantization algorithm, CQ, is presented, which includes two phases. The first phase reduces the number of colors by reducing the spatial resolution of the input image. The second phase furthermore reduces the number of colors by performing color clustering guided by distance information. Then, color mapping completes the process. The a...

We present a color image segmentation algorithm, RCRM, based on the detection of Representative Colors and on Region Merging. The 3D color histogram of the RGB input image is built. Colors are processed in decreasing frequency order and a grouping process is accomplished to gather in the same cluster all colors that are close enough to the current...

A technique for color quantization is described, which consists of two processes. The first process is based on the analysis of the histograms of the three color components of the RGB input image. The second process performs clustering of the colors quantized by the first process, based on their Euclidean distance. At the end of the second process,...

A color quantization algorithm is presented, which is based on the reduction of the spatial resolution of the input image. The maximum number of colors nf desired for the output image is used to fix the proper spatial resolution reduction factor. This is used to build a lower resolution version of the input image with size nf. Colors found in the l...

We present an interpolation algorithm for adaptive color image zooming. The algorithm produces the magnified image in one scan of the input image, and is fully automatic since does not involve any a priori fixed threshold. Given any integer zooming factor n, each pixel of the input image generates an n×n block of pixels in the zoomed image. For the...

An algorithm is presented to segment a color image based on the 3D histogram of colors. The peaks in the histogram, i.e., the connected components of colors with locally maximal occurrence, are detected. Each peak is associated a representative color, which is the color of the centroid of the peak. Peaks are processed in decreasing occurrence order...

A new technique for color reduction is presented, based on the analysis of the histograms of an image at different resolutions. Given an input image, lower resolution images are generated by using a scaling down interpolation method. Then, peaks and pits that are present in the histograms at all resolutions and dominate in the histogram of the inpu...

A color quantization method is presented, which is based on the analysis of the histogram at different resolutions computed on a Gaussian pyramid of the input image. Criteria based on persistence and dominance of peaks and pits of the histograms are introduced to detect the modes in the histogram of the input image and to define the reduced colorma...

A new segmentation method is suggested to distinguish the foreground from the background in gray-level images. The method is based on a 2-step process, respectively employing non-topological pixel removal (non-topological erosion) and topological region growing (topological expansion). The first step is aimed at identifying suitable seeds, correspo...

In this paper we build a shape preserving resolution pyramid and use it in the framework of image segmentation via watershed transformation. Our method is based on the assumption that the most significant image components perceived at high resolution will also be perceived at lower resolution. Thus, we detect the seeds for the watershed transformat...

Multi-scale skeletons can be conveniently employed in the matching phase of a recognition task. The multi-scale skeletons are here obtained by first computing the skeleton at all levels of a resolution structure and then establishing a hierarchy among skeleton components at different scales, using a parent-child relationship. Although subsets of th...

We introduce a method to reduce oversegmentation in watershed partitioned images, that is based on the use of a multiresolution representation of the input image. The underlying idea is that the most significant components perceived in the highest resolution image will remain identifiable also at lower resolution. Thus, starting from the image at t...

Summary form only given. The aim of this paper is to accomplish a prototype system for automatic data management able to support project activities in the field of architecture and engineering, in addition to improving the performance of existing software. This automatic data management consists of both consulting and sharing operations that favour...

A method to identify grey level image components, suitable for multi-scale analysis, is presented. Generally, a single threshold is not sufficient to separate components, perceived as individual entities. Our process is based on iterated identification and removal of pixels, with different grey level values, causing merging of grey level components...

A method to single out foreground components in a grey level image and to build a shift invariant and topology preserving pyramid is presented. A single threshold is generally not enough to separate foreground components, perceived as individual entities. Our process is based on iterated identification and removal of pixels causing merging of foreg...

The paper presents a novel procedure to hierarchically decompose a multiscale discrete skeleton. The skeleton is a linear pattern representation that is generally recognized as a good shape descriptor. For discrete images, the discrete skeleton is often preferable. Multiresolution representations are convenient for many image analysis tasks. Our re...

Starting from a binary digital image, a multi-valued pyramid is built and suitably treated, so that shape and topology properties of the pattern are preserved satisfactorily at all resolution levels. The multi-valued pyramid can then be used as input data to any grey-level skeletonization algorithm. In this way, a multi-resolution skeleton is compu...

An algorithm to decompose hierarchically bidimensional patterns is introduced. The single-scale input pattern is first transformed into a multi-scale data set. The multi-resolution skeleton is then computed and its hierarchical decomposition is obtained by using the notion of permanence. A constrained reverse distance transformation is applied to t...

Binary pyramids in two and three dimensions can be used for multiresolution representation. The "standard" OR and AND pyramids have serious drawbacks, as they distort the shape significantly; therefore they can seldom be used effectively. Here we present alternative approaches to build binary pyramids, aimed at improving shape preservation (and, as...

Coarse-to-fine skeletons of digital patterns in binary images are computed on a grey-level pyramid. This is built in such a way that pattern shape and topology are preserved at all resolution levels, as faithfully as possible. A key problem is spurious holes, created at lower resolutions by region merging, that would originate spurious loops in coa...

In a gray-tone digital picture, the skeleton is a set of digital lines mainly located in correspondence with the regions having locally higher gray-values. We describe a sequential skeletonization algorithm based on the dilation of the bottom regions, accomplished by an ordered propagation technique through increasing gray-levels. The non-bottom re...

The analysis of a 2D graphical document can be accomplished by using a suitable linear representation, e.g. the skeleton, of the pattern included in the document. Multiresolution representation and description are desirable for pattern recognition applications, as it reduces the complexity of the matching phase. In this paper, multiresolution shape...

We describe a procedure to create an abstraction of a grey-tone pattern by sketching its regions which have locally higher intensities. The sketch is a set of simple digital lines, qualitatively analogous to the skeleton representation computed in the case of a single-valued pattern. The grey-tone pattern is regarded as constituted by a number of r...

Binary pyramids can be used for multiresolution pattern representation. The two standard pyramids schemes, OR- and AND-pyramids, have, however, serious drawbacks, as they distort the shape significantly. In OR-pyramids black pixels spread all over the array due to expansion and merging of close regions. The shape of the original pattern is rapidly...

A two-stage procedure for direct vectorization of gray-level line patterns, that bypasses the binarization phase, is illustrated. The first stage extracts the gray-skeleton of the pattern as the set of one-pixel thick subsets placed in correspondence with locally higher intensity regions. The second stage removes skeleton subsets that are noninform...

A procedure useful to give evidence to the perceived linear structure of a gray-tone pattern is presented, which allows one to delineate its locally higher intensity regions with a connected set of simple digital lines, qualitatively analogous to the skeleton representation computed in the case of binary images. The pattern is regarded as constitut...

The grey-skeleton is understood as a connected subset of a grey-scale pattern, which is a stylized version consisting of a network of digital lines centrally placed along local higher intensity regions. We present a parallel thinning algorithm that relies on the iterated erosion of the pattern, and which proceeds from lower grey values towards high...

An algorithm is described to detect a number of points, on the contour of a planar shape, which constitute the vertices of a schematic polygonal representation of the shape itself. A set of points, initially extracted from the chain-coded representation of the contour, is iteratively examined, while removing some points and inserting new ones. The...