DocStormer: Revitalizing Multi-Degraded Colored Document Images to Pristine PDF

For capturing colored document images, e.g. posters and magazines, it is common that multiple degradations such as shadows, wrinkles, etc., are simultaneously introduced due to external factors. Restoring multi-degraded colored document images is a great challenge, yet overlooked, as most existing algorithms focus on enhancing color-ignored document images via binarization. Thus, we propose DocStormer, a novel algorithm designed to restore multi-degraded colored documents to their potential pristine PDF. The contributions are: firstly, we propose a "Perceive-then-Restore" paradigm with a reinforced transformer block, which more effectively encodes and utilizes the distribution of degradations. Secondly, we are the first to utilize GAN and pristine PDF magazine images to narrow the distribution gap between the enhanced results and PDF images, in pursuit of less degradation and better visual quality. Thirdly, we propose a non-parametric strategy, PFILI, which enables a smaller training scale and larger testing resolutions with acceptable detail trade-off, while saving memory and inference time. Fourthly, we are the first to propose a novel Multi-Degraded Colored Document image Enhancing dataset, named MD-CDE, for both training and evaluation. Experimental results show that the DocStormer exhibits superior performance, capable of revitalizing multi-degraded colored documents into their potential pristine digital versions, which fills the current academic gap from the perspective of method, data, and task

Advanced Image Acquisition, Processing Techniques and Applications

"Advanced Image Acquisition, Processing Techniques and Applications" is the first book of a series that provides image processing principles and practical software implementation on a broad range of applications. The book integrates material from leading researchers on Applied Digital Image Acquisition and Processing. An important feature of the book is its emphasis on software tools and scientific computing in order to enhance results and arrive at problem solution

Noise-Enhanced Information Systems

Noise, traditionally defined as an unwanted signal or disturbance, has been shown to play an important constructive role in many information processing systems and algorithms. This noise enhancement has been observed and employed in many physical, biological, and engineered systems. Indeed stochastic facilitation (SF) has been found critical for certain biological information functions such as detection of weak, subthreshold stimuli or suprathreshold signals through both experimental verification and analytical model simulations. In this paper, we present a systematic noise-enhanced information processing framework to analyze and optimize the performance of engineered systems. System performance is evaluated not only in terms of signal-to-noise ratio but also in terms of other more relevant metrics such as probability of error for signal detection or mean square error for parameter estimation. As an important new instance of SF, we also discuss the constructive effect of noise in associative memory recall. Potential enhancement of image processing systems via the addition of noise is discussed with important applications in biomedical image enhancement, image denoising, and classification

The Church of S. Maria Delle Palate in Tusa (Messina, Italy): Digitization and Diagnostics for a New Model of Enjoyment

Cultural places represent the tangible part of the identity and historical heritage of a civilization as well as an extraordinary driving force for the economic development of a country. Within its huge asset, Italy counts a wide number of archaeological sites and monuments which, despite their cultural value, are totally cut off from the most important cultural routes. This paper aims to demonstrate how specific actions of digitization can contribute to valorize (restoring a cultural value) ‘marginal’ landmarks, promoting their knowledge and inclusion. The case study described is represented by the Church of “Santa Maria delle Palate”, located inside the well-known Archaeological Park of Halaesa Arconidea (Tusa, ME). The church, built in 1551 and subject to several renovations throughout the centuries, has been investigated as part of an interdisciplinary training and skill transfer project carried out by a CNR-IPCF research team. During the activities, the group of trainees approached a multi-analytic method for the study of many Sicilian places using different techniques such as laser scanning, photogrammetry, thermography and spectroscopy and collecting a large amount of information and data. In 2019, the building in question was the object of a complete architectural survey in order to obtain an accurate digital replica; moreover, the wall painting representing St. Francis, preserved in the southern nave, was investigated through non-invasive investigations (IR-imaging, XRF and Raman spectrometry) with the intention of collecting information about its state of preservation and nature of pigments used and help the restoration work, which would have been carried out in the following months. The result of the work is a combined “digital archive” useful not only for the purposes of conservation, monitoring and dissemination, but as a container of information enjoyable at different levels of depth. In addition to the scientific outcomes achieved for the study of the painting, relevant from the historical and artistic point of view, we must underline the importance of the work for the implementation of a web-based platform where expert and inexpert users can virtually access the church virtual tour and search for specialized contents (e.g., measures, analyzes results). Media such as this are finally demonstrated to be able to promote the inclusion (e.g., for people unable to reach the place or with reducing mobility) and accessibility to cultural places during ordinary (maintenance, closure) or extraordinary events (pandemic)