High resolution airborne or vehicular imaging systems are often limited in performance by mechanical vibrations. High vibration frequency MTF is known. Low vibration frequency MTF is a random process analyzed here. Average and ideal maximum spatial frequency limitations are calculated. Plots are presented to describe the number of independent images of the same object that are required in order that at least one "lucky shot" with a given spatial frequency requirement is obtained with a given probability. Examples for short and long relative exposures are included. This data can be used to statistically define expected performance of high resolution systems and to aid accordingly in sensor selection. Probability of achieving higher resolution improves noticeably if relative exposure time is decreased.

Image Resolution Limits Resulting From Mechanical Vibrations

A recently developed method for the restoration of motion- blurred images is investigated and implemented for the special compli- cated case of image blur due to sinusoidal vibrations. Sinusoidal vibra- tions are analyzed in the context of blur identification and image restoration. The extent of the blur and the optical transfer function (OTF) are identified from the blurred image by a straightforward process with- out the use of iterative techniques. The blurred image is restored using a simple Wiener filter with the identified OTF. The main novel achievement is the use of only a single vibrated blurred image as input information, on which the restoration process is based. The various cases of blur types that depend on the imaging conditions are considered. Examples of blur identification and image restoration are presented. © 2000 Society of Photo- Optical Instrumentation Engineers. (S0091-3286(00)01408-2)

Restoration of an image degraded by vibrations using only a single frame

In many applications such as in airborne and terrestrial reconnaissance, robotics, medical imaging, and machine vision systems, the images of a video sequence are severely distorted by vibrations. Superresolution algorithms are suitable for restoring an image from a lowfrequency vibrated sequence because of high correlation between the frames and inherent interframe motion. However, we show that superresolution algorithms, which were developed for general types of blur, should be adapted to the specific characteristics of low-frequency vibration blur. We demonstrate that in the case of image sequences distorted by vibration, the images should be selected prior to processing. We find empirical selection criteria and propose a selection procedure.

Restoration and resolution enhancement of a single image from a vibration-distorted image sequence

This paper investigates the removal of line scratches from old movies and gives a twofold contribution. First, it presents simple technique for detecting the scratches, based on an analysis of the statistics of the grey levels. Second, the scratch removal is approached as an optimisation problem, and it is solved by using a genetic algorithm. The method can be classified as a static approach, as it works independently on each single frame of the sequence. It does not require any a-priori knowledge of the absolute position of the scratch, nor an external starting population of chromosomes for the genetic algorithm. The central column of the line scratch once detected is changed with a conventional linear interpolation; this transformation is the starting point of the optimisation process.

Scratch detection and removal from static images using simple statistics and genetic algorithms

This paper investigates the removal of line scratches from old films and gives a twofold contribution. First, a simple technique for detecting the scratches is proposed. This proposed method firstly applies a linear technique to enhance the scratches, and then detects the scratches using information in frames. Second, the scratch removal is approached as an inpainting problem, and it is solved by using an inpainting algorithm based on p-Laplace operator. In our experiment with old Chinese films, we show that our scheme not only obtains more accurate detection of scratches, but also gives better video quality.

An Efficient Scratches Detection and Inpainting Algorithm for Old Film Restoration

This paper deals with the restoration of images blurred as a result of image motion or vibration The key for restoration algorithm success is to derive accurately the Optical Transfer Function (OTF) representing the image motion degradation in the spatial frequency domain The basic method of obtaining the OTF from the relative displacement between the camera and the object using a motion sensor has been developed recently and is discussed elsewhere In this paper, the motion function is derived instead from analysis of a sequence of images The first step is to obtain the image motion information from the sequence of images according to two well known algorithms - the Block Matching Algorithm (BMA) and Edge Trace Tracking (ETT) The basis for these two methods consists of tracking a block or an edge through a sequence of several images The results of these two methods were fitted to a sinusoidal function, compared, and there was excellent agreement between them Finally, the image is restored using the OTF obtained from the tracking method

M. Robbins

Papers

Image motion restoration from a sequence of images