This paper proposes a novel approach for the completion of natural scenery images, which automatically detects the blemish region in the image for restoration. This approach consists of two filtering steps and uses shape information to detect the blemish region. Then, the detected regions are marked with a specified color, so that image completion is conveniently implemented in the area we dete...

3D video and the corresponding applications are getting more and more attentions in the recent years due to the vivid viewing experiment it can bring. In a 3DTV system, the occlusion handling is one main design challenge. The quality of the previous works is not good enough. Further, the computational complexity from the image based processing grows dramatically while the requirement of the vir...

It is now generally recognized that user-provided image tags are incomplete and noisy. In this study, we focus on the problem of tag completion that aims to simultaneously enrich the missing tags and remove noisy tags. The novel component of the proposed framework is a noisy matrix recovery algorithm. It assumes that the observed tags are independently sampled from an unknown tag matrix and our...

Recently, image categorization has been an active research topic due to the urgent need to retrieve and browse digital images via semantic keywords. This paper formulates image categorization as a multi-label classification problem using recent advances in matrix completion. Under this setting, classification of testing data is posed as a problem of completing unknown label entries on a data ma...

Image completion involves filling missing parts in images. In this paper we address this problem through the statistics of patch offsets. We observe that if we match similar patches in the image and obtain their offsets (relative positions), the statistics of these offsets are sparsely distributed. We further observe that a few dominant offsets provide reliable information for completing the im...

The problem of tag completion is to learn the missing tags of an image. In this paper, we propose to learn a tag scoring vector for each image by local linear learning. A local linear function is used in the neighborhood of each image to predict the tag scoring vectors of its neighboring images. We construct a unified objective function for the learning of both tag scoring vectors and local lin...

When browsing through photographs taken during a trip, it can be a distressing discovery to find many other bystanders captured within the frame. A visually compelling snapshot preserves the desired subject in the foreground, and eliminates irrelevant persons or objects. In this paper, we present a new image completion algorithm that retains the geometric consistency of the scene using Internet...

Multi-image segmentation makes use of global and local features in an attempt to classify every pixel in an image into a semantic region. One important relationship is inter-class spacial interaction between small local regions we call “superpixels”. While complex models have been built in order to provide for such semantic understanding and define visual grammars, we explore the usefulness of ...

This paper presents a novel gradient-based image completion algorithm for removing significant objects from natural images or photographs. Our method reconstructs the region of removal in two phases. Firstly, the gradient maps in the removed area are completed through a patch based filling algorithm. After that, the image is reconstructed from the gradient maps by solving a Poisson equation. A ...