Real-time Global Illumination Decomposition of Videos

We propose the first approach for the decomposition of a monocular color video into direct and indirect illumination components in real time. We retrieve, in separate layers, the contribution made to the scene appearance by the scene reflectance, the light sources and the reflections from various coherent scene regions to one another. Existing techniques that invert global light transport require image capture under multiplexed controlled lighting, or only enable the decomposition of a single image at slow off-line frame rates. In contrast, our approach works for regular videos and produces temporally coherent decomposition layers at real-time frame rates. At the core of our approach are several sparsity priors that enable the estimation of the per-pixel direct and indirect illumination layers based on a small set of jointly estimated base reflectance colors. The resulting variational decomposition problem uses a new formulation based on sparse and dense sets of non-linear equations that we solve efficiently using a novel alternating data-parallel optimization strategy. We evaluate our approach qualitatively and quantitatively, and show improvements over the state of the art in this field, in both quality and runtime. In addition, we demonstrate various real-time appearance editing applications for videos with consistent illumination

Remote sensing satellite image processing techniques for image classification: a comprehensive survey

This paper is a brief survey of advance technological aspects of Digital Image Processing which are applied to remote sensing images obtained from various satellite sensors. In remote sensing, the image processing techniques can be categories in to four main processing stages: Image preprocessing, Enhancement, Transformation and Classification. Image pre-processing is the initial processing which deals with correcting radiometric distortions, atmospheric distortion and geometric distortions present in the raw image data. Enhancement techniques are applied to preprocessed data in order to effectively display the image for visual interpretation. It includes techniques to effectively distinguish surface features for visual interpretation. Transformation aims to identify particular feature of earth’s surface and classification is a process of grouping the pixels, that produces effective thematic map of particular land use and land cover

PaletteNeRF: Palette-based Color Editing for NeRFs

Neural Radiance Field (NeRF) is a powerful tool to faithfully generate novel views for scenes with only sparse captured images. Despite its strong capability for representing 3D scenes and their appearance, its editing ability is very limited. In this paper, we propose a simple but effective extension of vanilla NeRF, named PaletteNeRF, to enable efficient color editing on NeRF-represented scenes. Motivated by recent palette-based image decomposition works, we approximate each pixel color as a sum of palette colors modulated by additive weights. Instead of predicting pixel colors as in vanilla NeRFs, our method predicts additive weights. The underlying NeRF backbone could also be replaced with more recent NeRF models such as KiloNeRF to achieve real-time editing. Experimental results demonstrate that our method achieves efficient, view-consistent, and artifact-free color editing on a wide range of NeRF-represented scenes.Comment: 12 pages, 10 figure

Hyperspectral image analysis for questioned historical documents.

This thesis describes the application of spectroscopy and hyperspectral image processing to examine historical manuscripts and text. Major activities in palaeographic and manuscript studies include the recovery of illegible or deleted text, the minute analyses of scribal hands, the identification of inks and the segmentation and dating of text. This thesis describes how Hyperspectral Imaging (HSI), applied in a novel manner, can be used to perform quality text recovery, segmentation and dating of historical documents. The non-destructive optical imaging process of Spectroscopy is described in detail and how it can be used to assist historians and document experts in the exemption of aged manuscripts. This non-destructive optical method of analysis can distinguish subtle differences in the reflectance properties of the materials under study. Many historically significant documents from libraries such as the Royal Irish Academy and the Russell Library at the National University of Ireland, Maynooth, have been the selected for study using the hyperspectral imaging technique. Processing techniques have are described for the applications to the study of manuscripts in a poor state of conservation. The research provides a comprehensive overview of Hyperspectral Imaging (HSI) and associated statistical and analytical methods, and also an in-depth investigation of the practical implementation of such methods to aid document analysts. Specifically, we provide results from employing statistical analytical methods including principal component analysis (PCA), independent component analysis (ICA) and both supervised and automatic clustering methods to historically significant manuscripts and text VIII such as Leabhar na hUidhre, a 12th century Irish text which was subject to part-erasure and rewriting, a 16th Century pastedown cover, and a multi-ink example typical of that found in, for example, late medieval administrative texts such as Gttingen’s kundige bok. The purpose of which is to achieve an overall greater insight into the historical context of the document, which includes the recovery or enhancement of faded or illegible text or text lost through fading, staining, overwriting or other forms of erasure. In addition, we demonstrate prospect of distinguishing different ink-types, and furnishing us with details of the manuscript’s composition, all of which are refinements, which can be used to answer questions about date and provenance. This process marks a new departure for the study of manuscripts and may provide answer many long-standing questions posed by palaeographers and by scholars in a variety of disciplines. Furthermore, through text retrieval, it holds out the prospect of adding considerably to the existing corpus of texts and to providing very many new research opportunities for coming generations of scholars

Text-guided Image-and-Shape Editing and Generation: A Short Survey

Image and shape editing are ubiquitous among digital artworks. Graphics algorithms facilitate artists and designers to achieve desired editing intents without going through manually tedious retouching. In the recent advance of machine learning, artists' editing intents can even be driven by text, using a variety of well-trained neural networks. They have seen to be receiving an extensive success on such as generating photorealistic images, artworks and human poses, stylizing meshes from text, or auto-completion given image and shape priors. In this short survey, we provide an overview over 50 papers on state-of-the-art (text-guided) image-and-shape generation techniques. We start with an overview on recent editing algorithms in the introduction. Then, we provide a comprehensive review on text-guided editing techniques for 2D and 3D independently, where each of its sub-section begins with a brief background introduction. We also contextualize editing algorithms under recent implicit neural representations. Finally, we conclude the survey with the discussion over existing methods and potential research ideas.Comment: 10 page