Ringing artifacts refer to the noisy-looking vicinity of edges that are supposed to belong to a smooth object. In this paper, we propose a no-reference method to measure the visual impact of ringing artifacts for JPEG images. Unlike previous work, we perform a global analysis on the smooth regions in a JPEG image and classify them into different objects according to their colors and texture characteristics. We study the region activity for each type of the object in the image and assign an appropriate proxy object to each potential ringing region adjacent to an edge. The contrast between the noise levels of the ringing regions and their proxies are used to determine the visual impact of the ringing artifact. Finally, a ringing feature is computed for each edge pixel based on the feature values of the ringing artifacts in a local window. We thus obtain a ringing map to indicate the visibility of local ringing artifacts. Our preliminary results show a consistency between our model and the visual impact of the ringing artifacts.
A robust, invisible watermarking scheme is proposed for digital images, where the watermark is embedded using the block-based lapped orthogonal transform (LOT). The embedding process follows a spread spectrum watermarking approach. In contrast to the use of transforms such as discrete cosine transform, our LOT watermarking scheme allows larger watermark embedding energy while maintaining the same level of subjective invisibility. In particular, the use of LOT reduces block artifacts caused by the insertion of the watermark in a block-by-block manner, hence obtaining a better balance between invisibility and robustness. Moreover, we use a human visual system (HVS) model to adaptively adjust the energy of the watermark during embedding. In our HVS model, each block is categorized into one of four classes (texture, fine-texture, edge, and plain-area) by using a feature known as the texture masking energy. Blocks with edges are also classified according to the edge direction. The block classification is used to adjust the watermark embedding parameters for each block.
In this paper, a novel method is proposed to locate one-dimensional barcodes in JPEG 2000 images. The barcode
locating system consists of two parts: candidate barcode location detection, barcode location verification and
refinement. Both parts are designed to work in the compressed domain of JPEG 2000 images. The locations of
candidate barcodes are extracted from the header data and verified by examining part of the decoded coefficients of the
JPEG 2000 file. Since only a small amount of the compressed data is used, this algorithm has a low complexity relative
to algorithms which use all of the pixel data.
A robust, invisible watermarking scheme is proposed for digital images, where the watermark is embedded
using the block-based Lapped Orthogonal Transform (LOT). The embedding process follows a spread spectrum
watermarking approach. In contrast to the use of transforms such as DCT, our LOT watermarking scheme allows
larger watermark embedding energy while maintaining the same level of subjective invisibility. In particular, the
use of LOT reduces block artifacts caused by the insertion of the watermark in a block-by-block manner, hence
obtaining a better balance between invisibility and robustness. Moreover, we use a human visual system (HVS)
model to adaptively adjust the energy of the watermark during embedding. In our HVS model, each block is
categorized into one of four classes (texture, fine-texture, edge, and plain-area) by using a feature known as the
Texture Masking Energy (TME). Blocks with edges are also classified according to the edge direction. The block
classification is used to adjust the watermark embedding parameters for each block.
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