66 research outputs found
Removal Of Blocking Artifacts From JPEG-Compressed Images Using An Adaptive Filtering Algorithm
The aim of this research was to develop an algorithm that will produce a considerable improvement in the quality of JPEG images, by removing blocking and ringing artifacts, irrespective of the level of compression present in the image. We review multiple published related works, and finally present a computationally efficient algorithm for reducing the blocky and Gibbs oscillation artifacts commonly present in JPEG compressed images. The algorithm alpha-blends a smoothed version of the image with the original image; however, the blending is controlled by a limit factor that considers the amount of compression present and any local edge information derived from the application of a Prewitt filter. In addition, the actual value of the blending coefficient (α) is derived from the local Mean Structural Similarity Index Measure (MSSIM) which is also adjusted by a factor that also considers the amount of compression present. We also present our results as well as the results for a variety of other papers whose authors used other post compression filtering methods
Recovering Sign Bits of DCT Coefficients in Digital Images as an Optimization Problem
Recovering unknown, missing, damaged, distorted or lost information in DCT
coefficients is a common task in multiple applications of digital image
processing, including image compression, selective image encryption, and image
communications. This paper investigates recovery of a special type of
information in DCT coefficients of digital images: sign bits. This problem can
be modelled as a mixed integer linear programming (MILP) problem, which is
NP-hard in general. To efficiently solve the problem, we propose two
approximation methods: 1) a relaxation-based method that convert the MILP
problem to a linear programming (LP) problem; 2) a divide-and-conquer method
which splits the target image into sufficiently small regions, each of which
can be more efficiently solved as an MILP problem, and then conducts a global
optimization phase as a smaller MILP problem or an LP problem to maximize
smoothness across different regions. To the best of our knowledge, we are the
first who considered how to use global optimization to recover sign bits of DCT
coefficients. We considered how the proposed methods can be applied to
JPEG-encoded images and conducted extensive experiments to validate the
performances of our proposed methods. The experimental results showed that the
proposed methods worked well, especially when the number of unknown sign bits
per DCT block is not too large. Compared with other existing methods, which are
all based on simple error-concealment strategies, our proposed methods
outperformed them with a substantial margin, both according to objective
quality metrics (PSNR and SSIM) and also our subjective evaluation. Our work
has a number of profound implications, e.g., more sign bits can be discarded to
develop more efficient image compression methods, and image encryption methods
based on sign bit encryption can be less secure than we previously understood.Comment: 13 pages, 8 figure
PERBAIKAN CITRA DENGAN NOISE MISSING BLOCK MENGGUNAKAN IMPLEMENTASI ALGORITMA PROJECTION ONTO CONVEX SETS (POCS)
Ketajaman kualitas gambar sangat diperlukan untuk melihat dan mengamati gambar dengan jelas tanpa gangguan seperti blur atau noise. Dalam proses pengiriman atau penyimpanan, gambar dapat terganggu dalam bentuk kerusakan pada bagian-bagian tertentu yang hilang atau blok-blok piksel, kerusakan ini adalah bentuk utama dari kesalahan dalam suatu gambar. Jadi dengan mengimplementasikan algoritma rekonstruksi citra Projection Onto Convex Sets (POCS) pada domain Discrete Cosine Transform (DCT) untuk meningkatkan citra, terutama gambar yang mengalami kerusakan pada beberapa bagian yang hilang atau blok piksel. Untuk blok proses pemulihan ada beberapa langkah yang harus diambil termasuk deteksi garis, pembacaan jendela di sekitarnya dan vektor pemulihan. Dari hasil pengujian dapat disimpulkan bahwa metode ini dapat digunakan untuk pemulihan blok POCS dan nilai-nilai piksel yang sesuai dengan blok warna di sekitar blok. Pengukuran nilai kesalahan citra menggunakan Mean Square Error (MSE) dan Peak Signal to Noise Ratio (PSNR)
Edge-guided image gap interpolation using multi-scale transformation
This paper presents improvements in image gap restoration through the incorporation of edge-based directional interpolation within multi-scale pyramid transforms. Two types of image edges are reconstructed: 1) the local edges or textures, inferred from the gradients of the neighboring pixels and 2) the global edges between image objects or segments, inferred using a Canny detector. Through a process of pyramid transformation and downsampling, the image is progressively transformed into a series of reduced size layers until at the pyramid apex the gap size is one sample. At each layer, an edge skeleton image is extracted for edge-guided interpolation. The process is then reversed; from the apex, at each layer, the missing samples are estimated (an iterative method is used in the last stage of upsampling), up-sampled, and combined with the available samples of the next layer. Discrete cosine transform and a family of discrete wavelet transforms are utilized as alternatives for pyramid construction. Evaluations over a range of images, in regular and random loss pattern, at loss rates of up to 40%, demonstrate that the proposed method improves peak-signal-to-noise-ratio by 1–5 dB compared with a range of best-published works
Reduction of blocking artifacts using side information
Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2006.Includes bibliographical references (p. 95-96).Block-based image and video coding systems are used extensively in practice. In low bit-rate applications, however, they suffer from annoying discontinuities, called blocking artifacts. Prior research shows that incorporating systems that reduce blocking artifacts into codecs is useful because visual quality is improved. Existing methods reduce blocking artifacts by applying various post-processing techniques to the compressed image. Such methods require neither any modification to current encoders nor an increase in the bit-rate. This thesis examines a framework where blocking artifacts are reduced using side information transmitted from the encoder to the decoder. Using side information enables the use of the original image in deblocking, which improves performance. Furthermore, the computational burden at the decoder is reduced. The principal question that arises is whether the gains in performance of this choice can compensate for the increase in the bit-rate due to the transmission of side information. Experiments are carried out to answer this question with the following sample system: The encoder determines block boundaries that exhibit blocking artifacts as well as filters (from a predefined set of filters) that best deblock these block boundaries.(cont.) Then it transmits side information that conveys the determined block boundaries together with their selected filters to the decoder. The decoder uses the received side information to perform deblocking. The proposed sample system is compared against an ordinary coding system and a post-processing type deblocking system with the bit-rate of these systems being equal to the overall bit-rate (regular encoding bits + side information bits) of the proposed system. The results of the comparisons indicate that, both for images and video sequences, the proposed system can perform better in terms of both visual quality and PSNR for some range of coding bit-rates.by Fatih Kamisli.S.M
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Multi-scale edge-guided image gap restoration
This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University London.The focus of this research work is the estimation of gaps (missing blocks) in digital images. To progress the research two main issues were identified as (1) the appropriate domains for image gap restoration and (2) the methodologies for gap interpolation. Multi-scale transforms provide an appropriate framework for gap restoration. The main advantages are transformations into a set of frequency and scales and the ability to progressively reduce the size of the gap to one sample wide at the transform apex. Two types of multi-scale transform were considered for comparative evaluation; 2-dimensional (2D) discrete cosines (DCT) pyramid and 2D discrete wavelets (DWT). For image gap estimation, a family of conventional weighted interpolators and directional edge-guided interpolators are developed and evaluated. Two types of edges were considered; ‘local’ edges or textures and ‘global’ edges such as the boundaries between objects or within/across patterns in the image. For local edge, or texture, modelling a number of methods were explored which aim to reconstruct a set of gradients across the restored gap as those computed from the known neighbourhood. These differential gradients are estimated along the geometrical vertical, horizontal and cross directions for each pixel of the gap. The edge-guided interpolators aim to operate on distinct regions confined within edge lines. For global edge-guided interpolation, two main methods explored are Sobel and Canny detectors. The latter provides improved edge detection. The combination and integration of different multi-scale domains, local edge interpolators, global edge-guided interpolators and iterative estimation of edges provided a variety of configurations that were comparatively explored and evaluated. For evaluation a set of images commonly used in the literature work were employed together with simulated regular and random image gaps at a variety of loss rate. The performance measures used are the peak signal to noise ratio (PSNR) and structure similarity index (SSIM). The results obtained are better than the state of the art reported in the literature
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