Content-aware resizing methods have recently been developed, among which, seam-carving has achieved the most widespread use. Seam-carving’s versatility enables deliberate object removal and benign image resizing, in which perceptually important content is preserved. Both types of modifications compromise the utility and validity of the modified images as evidence in legal and journalistic appli...

Seam carving is a powerful retargeting algorithm for mapping images to arbitrary sizes with arbitrary aspect ratios. Meanwhile, the seamlet transform has been introduced as an efficient image representation for seam-carving-based retargeting over heterogeneous multimedia devices with a broad range of display sizes. The original seamlet transform was developed using Haar filters, and hence it en...

Based on rapid upsurge in the demand and usage of electronic media devices such as tablets, smart phones, laptops, personal computers, etc. and its different display specifications including the size and shapes, image retargeting became one of the key components of communication technology and internet. The existing techniques in image resizing cannot save the most valuable information of image...

SUMMARY Seam carving, which preserves semantically important image content during resizing process, has been actively researched in recent years. This paper proposes a novel forensic technique to detect the trace of seam carving. We exploit the energy bias and noise level of images under analysis to reliably unveil the evidence of seam carving. Furthermore , we design a detector investigating t...

In this paper, we propose a new method to adapt the resolution of images to the limited display resolution of mobile devices. We use the seam carving technique to identify and remove less relevant content in images. Seam carving achieves a high adaptation quality for landscape images and distortions caused by the removal of seams are very low compared to other techniques like scaling or croppin...

(a) Input image (b) Scaling (c) Visibility map for (d) (d) Seam carving (e) Visibility map for (f) (f) Seam carving energy terms (distortion energy: absolute magnitude distance, nD = 1) (g) Visibility map for (h) (h) Distortion energy: absolute magnitude distance, nD = 1; unary with nU = 1 (i) Visibility map for (j) (j) Distortion energy: absolute magnitude distance, nD = 1; seam term: repeat c...

ABSTRACT When changing height and width of image traditional techniques for image resizing are oblivious to the content of image. A simple operator seam carving is used for image and video retargeting. This seam carving operator is used for content aware image resizing to reduce or expand image size. According to seam carving method every object in the image must be scaled down proportionally. ...

In this paper we consider the problem of implementing and optimizing the Seam Carving algorithm on graphics processing units. Seam Carving is a content-aware image resizing method proposed by Avidan and Shamir. In order to use their proposed method in real-time application, a pre-processing step is needed. While some other papers propose real-time resizing by changing the original Seam Carving ...

Let Ω1 and Ω2 be strongly pseudoconvex domains in C and f : Ω1 → Ω2 an isometry for the Kobayashi or Carathéodory metrics. Suppose that f extends as a C map to Ω̄1. We then prove that f |∂Ω1 : ∂Ω1 → ∂Ω2 is a CR or anti-CR diffeomorphism. It follows that Ω1 and Ω2 must be biholomorphic or anti-biholomorphic. The main tool is a metric version of the Pinchuk rescaling technique.

We study isometries of the Kobayashi and Carathéodory metrics on strongly pseudoconvex and strongly convex domains in C and prove: (i) Let Ω1 and Ω2 be strongly pseudoconvex domains in C and f : Ω1 → Ω2 an isometry. Suppose that f extends as a C map to Ω̄1. Then f |∂Ω1 : ∂Ω1 → ∂Ω2 is a CR or anti-CR diffeomorphism. Hence it follows that Ω1 and Ω2 must be biholomorphic or anti-biholomorphic. (ii)...