Guillermo Peris-Fajarnés

A fast impulsive noise color image filter using fuzzy metrics

In this paper, the problem of impulsive noise reduction in multichannel images is addressed. A new filter is proposed on the basis of a recently introduced family of computationally attractive filters with a good detail-preserving ability (FSVF). FSVF is based on privileging the central pixel in each filtering window in order to replace it only when it is really noisy and preserve the original undistorted image structures. The new filter is based on a novel fuzzy metric and it is created by combining the mentioned scheme and the fuzzy metric. The use of the fuzzy metric makes the filter computationally simpler and it allows to adjust the privilege of the central pixel giving the filter an adaptive nature. Moreover, it is shown that the new filter outperforms the classical-order statistics filtering techniques and its performance is similar to FSVF, outperforming it in some cases.

Local self-adaptive fuzzy filter for impulsive noise removal in color images

This paper describes a new filter for impulsive noise reduction in color images based on a recently introduced family of vector filters with a good ability for preserving details. These filters use a reduced ordering of color vectors in order to detect and replace impulses. The proposed filter uses local statistics to adapt itself to simultaneously remove impulses and preserve image edges and details. The proposed filtering technique is robust and achieves a good balance between noise attenuation and detail reservation. In addition, it outperforms well-known vector filtering solutions and produces visually pleasing filtered color images.

Isolating impulsive noise pixels in color images by peer group techniques

A new method for removing impulsive noise in color images is presented. The fuzzy metric peer group concept is used to build novel switching vector filters. In the proposed filtering procedure, a set of noise-free pixels of high reliability is determined by applying a highly restrictive condition based on the peer group concept. Afterwards, an iterative detection process is used to refine the initial findings by detecting additional noise-free pixels. Finally, noisy pixels are filtered by maximizing the employed fuzzy distance criterion between the pixels inside the filter window. Comparisons are provided to show that our approach suppresses impulsive noise, while preserving image details. In addition, the method is analyzed in order to justify the necessity of the iterative process and demonstrate the computational efficiency of the proposed approach.

New adaptive vector filter using fuzzy metrics

Classical nonlinear vector median-based filters are well-known methods for impulsive noise suppression in color images, but mostly they lack good detail-preserving ability. We use a class of fuzzy metrics to introduce a vector filter aimed at improving the detail-preserving ability of classical vector filters while effectively removing impulsive noise. The output of the proposed method is the pixel inside the filter window which maximizes the similarity in color and spatial closeness. The use of fuzzy metrics allows us to handle both criteria simultaneously. The filter is designed so that the importance of the spatial criterion can be adjusted. We show that the filter can adapt to the density of the contaminating noise by adjusting the spatial criterion importance. Classical and recent filters are used to assess the proposed filtering. The experimental results show that the proposed technique performs competitively.

A new vector median filter based on fuzzy metrics

Vector median filtering is a well known technique for reducing noise in color images. These filters are defined on the basis of a suitable distance or similarity measure, being the most common used the Euclidean and City-Block distances. In this paper, a Fuzzy Metric, in the sense of George and Veeramani (1994), is defined and applied to color image filtering by means of a new Vector Median Filter. It is shown that the standard Vector Median Filter is outperformed when using this Fuzzy Metric instead of the Euclidean and City-Block distances.

Sensory navigation device for blind people

This paper presents a new Electronic Travel Aid (ETA) ‘Acoustic Prototype’ which is especially suited to facilitate the navigation of visually impaired users. The device consists of a set of 3-Dimensional Complementary Metal Oxide Semiconductor (3-D CMOS) image sensors based on the three-dimensional integration and Complementary Metal-Oxide Semiconductor (CMOS) processing techniques implemented into a pair of glasses, stereo headphones as well as a Field-Programmable Gate Array (FPGA) used as processing unit. The device is intended to be used as a complementary device to navigation through both open known and unknown environments. The FPGA and the 3D-CMOS image sensor electronics control object detection. Distance measurement is achieved by using chip-integrated technology based on the Multiple Short Time Integration method. The processed information of the object distance is presented to the user via acoustic sounds through stereophonic headphones. The user interprets the information as an acoustic image of the surrounding environment. The Acoustic Prototype transforms the surface of the objects of the real environment into acoustical sounds. The method used is similar to a bat’s acoustic orientation. Having good hearing ability, with few weeks training the users are able to perceive not only the presence of an object but also the object form (that is, if the object is round, if it has corners, if it is a car or a box, if it is a cardboard object or if it is an iron or cement object, a tree, a person, a static or moving object). The information is continuously delivered to the user in a few nanoseconds until the device is shut down, helping the end user to perceive the information in real time.

Rank-Ordered differences statistic based switching vector filter

In this paper a new switching vector filter for impulsive noise removal in color images is proposed. The new method is based on a recently introduced impulse detector named Rank-Ordered Differences Statistic (ROD) which is adapted to be used in color images. The switching scheme between the identity operation and the Arithmetic Mean Filter is defined using the mentioned impulse detector. Extensive experiments show that the proposed technique is simple, easy to implement and significantly outperforms the classical vector filters presenting a competitive performance respect to recent impulsive noise vector filters.

Obstacle-Free Pathway Detection by Means of Depth Maps

The detection of surrounding obstacle-free space is an essential task for many intelligent automotive and robotic applications. In this paper we present a method to detect obstacle-free pathways in real-time using depth maps from a pair of stereo images. Depth maps are obtained by processing the disparity between left and right images from a stereo-vision system. The proposed technique assumes that depth of pixels in obstacle-free pathways should increase slightly and linearly from the bottom of the image to the top. The proposed real-time detection checks whether the depth of groups of image columns matches a linear model. Only pixels fulfilling the matching requirements are identified as obstacle-free pathways. Experimental results with real outdoor stereo images show that the method performance is promising.

Measurement of Aerodynamic Coefficients of Spherical Objects Using an Electro-optic Device

Aerodynamic coefficients are required to determine the trajectory of moving objects. These coefficients are typically obtained measuring the forces acting on the object using a wind tunnel. Wind tunnels are expensive and not easily available; therefore, their use is limited. This paper presents a new procedure to measure aerodynamic coefficients of spherical objects using an electro-optic device. Forces are calculated from velocity changes instead of being directly measured. The procedure is based on a method to measure the three components of the instantaneous velocity vector at known positions. The main advantages are size, cost and complexity reduction compared to wind tunnels. These advantages open the possibility of integration in production lines for quality control. A prototype has been built and tested using soccer balls.

Fuzzy Directional-Distance Vector Filter

A well-known family of nonlinear multichannel image filters uses the ordering of vectors by means of an appropriate distance or similarity measurebetween vectors. In this way, the vector median filter(VMF), the vector directional filter(VDF) and the distance directional filter(DDF) use the relative magnitude differences between vectors, the directional vector difference or a combination of both, respectively. In this paper, a novel fuzzy metricis used to measure magnitude and directional fuzzy distancesbetween image vectors. Then, a variant of the DDF using this fuzzy metricis proposed. The proposed variant is computationally cheaper than the classical DDF. In addition, experimental results show that the proposed filter receives better results in impulsive noise suppression in colour images.