Chandan Singh D. Rawat

Bio: Chandan Singh D. Rawat is an academic researcher from National Institute of Technology, Rourkela. The author has contributed to research in topics: Image compression & Set partitioning in hierarchical trees. The author has an hindex of 2, co-authored 5 publications receiving 60 citations.

A Hybrid Image Compression Scheme Using DCT and Fractal Image Compression

Abstract: Digital images are often used in several domains. Large amount of data is necessary to represent the digital images so the transmission and storage of such images are time-consuming and infeasible. Hence the information in the images is compressed by extracting only the visible elements. Normally the image compression technique can reduce the storage and transmission costs. During image compression, the size of a graphics file is reduced in bytes without disturbing the quality of the image beyond an acceptable level. Several methods such as Discrete Cosine Transform (DCT), DWT, etc. are used for compressing the images. But, these methods contain some blocking artifacts. In order to overcome this difficulty and to compress the image efficiently, a combination of DCT and fractal image compression techniques is proposed. DCT is employed to compress the color image while the fractal image compression is employed to evade the repetitive compressions of analogous blocks. Analogous blocks are found by using the Euclidean distance measure. Here, the given image is encoded by means of Huffman encoding technique. The implementation result shows the effectiveness of the proposed scheme in compressing the color image. Also a comparative analysis is performed to prove that our system is competent to compress the images in terms of Peak Signal to Noise Ratio (PSNR), Structural Similarity Index (SSIM) and Universal Image Quality Index (UIQI) measurements.

Selection of wavelet for image compression in hybrid coding scheme combining SPIHT-and SOFM-based vector quantisation

Abstract: Image compression is an important task for image transmission and storage. Thus far many compression techniques have been developed, such as transform image coding, predictive image coding, Vector Quantisation (VQ) and so on. Of these compression techniques, the techniques based on transform coding and VQ have received considerable attention. Recently, hybrid schemes for effective image compression have gained enormous popularity among researchers. In this paper, we analyse a hybrid scheme combining Kohonen’s Self-Organising Feature Map (SOFM)-based VQ coding and Set Partitioning In Hierarchical Trees (SPIHT) coding for compression of images (Rawat and Meher, 2009). The reconstructed image quality achieved after decoding depends upon the wavelet used in SPIHT. The effectiveness of the scheme for various orthogonal and biorthogonal wavelets for the hybrid scheme is tested in terms of Peak Signal-to-Noise Ratio (PSNR) and Visual Information Fidelity (VIF).

Modified pointwise shape-adaptive dct for high-quality deblocking of compressed images

Abstract: Blocking artifact is one of the most annoying artifacts in the image compression coding. In order to improve the quality of the reconstructed image several deblocking algorithms have been proposed. A high-quality modified image deblocking algorithm based on the shape-adaptive DCT (SA-DCT) is shown. The SA-DCT is a low-complexity transform which can be computed on a support of arbitrary shape. This transform has been adopted by the MPEG-4 standard and it is found implemented in modern video hardware. This approach has been used for the deblocking of block-DCT compressed images. In this paper we see modified pointwise SA-DCT method based on adaptive DCT threshold coefficient instead of constant DCT threshold coefficient used by the original pointwise SA-DCT method. Extensive simulation experiments attest the advanced performance of the proposed filtering method. The visual quality of the estimates is high, with sharp detail preservation, clean edges. Blocking artifacts are suppressed while salient image features are preserved.

A hybrid image compression scheme using HVS characteristics: combining SPIHT- and SOFM-based Vector Quantisation

Abstract: Nowadays, developing hybrid schemes for effective image compression has gained enormous popularity among researchers. A hybrid scheme combining Kohonen’s Self Organising Feature Map (SOFM) based Vector Quantisation (VQ) coding and Set Partitioning In Hierarchical Trees (SPIHT) coding for effective compression of images is proposed. This paper embeds Human Visual System (HVS) into SPIHT algorithm to proffer different perceptual weights to different image blocks. The SPIHT coder results with a bit stream, which is then fed to the SOFM, based VQ coding for compression. The experimental results demonstrate the improvement in CR and subjective visual quality of the images on reconstruction.

Mutual Coupling between Wire Scatterers Using Two Term Approximation

Abstract: The mutual coupling between two wire scatterers having exact current distribution that is in fact closer to cosinusoidal distribution is not available in the literature. In order to derive closed form expressions, the current is often crudely approximated using a piecewise sinusoidal distribution leading to inaccurate results. In this paper, the exact distribution on wire scatterers is approximated using a more accurate two term approximation. It has been shown that the results obtained using two term approximation are very close to the cosinusoidal distribution and much better than the widely used piecewise sinusoidal approximation (PWS). It has been shown that the error in mutual coupling evaluated using two term approximation is less than 1% for scatterer lengths up to 0.75λ as compared to an error of more than 4% for piecewise sinusoidal approximation. This analysis is useful in estimating the RCS or scattering from an array of parallel wire scatterers, analysis of Yagi-Uda antennas and arrays, Log Periodic dipole array, etc.

Enhanced Image Compression Using Fractal and Tree Seed-Bio Inspired Algorithm

Abstract: In the field of Image compression and particularly for the process of image encoding, Fractal image compression (FIC) technique plays a vital role. This technique is based on fractals present in an image and also it is capable of generating the copying blocks dependent on numerical changes. The only drawback in the Fractal image compression is that the time taken during the encoding process when the data is large. Thus, it is necessary to optimize the encoding process for efficient resource utilization as optimization algorithms are generally known for converging behavior. This research work attempts to apply the Tree Seed Algorithm as a characteristic enlivened high-level algorithm to improve FIC. Output shows the improvement of such calculation under various types (encoding time, pressure proportion, top sign to clamor proportion, and mean square error. Moreover, an examination with a portion of the current techniques underlines this addition.

Efficient HEVC steganography approach based on audio compression and encryption in QFFT domain for secure multimedia communication

Abstract: High-Efficiency Video Coding (HEVC) is the most recent video codec standard. It is substantial to analyze the HEVC steganography process due to its practical and academic significance. Thus, a secure HEVC steganography approach is introduced in this paper to study the possibility of hiding an encrypted secret audio message within a cover compressed video frame in a secure and complicated manner. In the preliminary stage, the secret audio message is compressed utilizing the Discrete Cosine Transform (DCT) to achieve a high capacity performance for the HEVC steganography process. After that, the suggested approach implies two-cascaded encryption layers to encrypt the compressed secret message before embedding it within a cover HEVC frame. In the first encryption layer, a novel encryption technique based on random projection and Legendre sequence in the Discrete Wavelet Transform (DWT) domain is introduced to cipher the compressed secret audio message. In the second encryption layer, the yielded encrypted audio message is represented in a form of quaternion numbers using the Quaternion Fast Fourier Transform (QFFT) technique. Each cover HEVC frame is also represented in a quaternion form. In the suggested approach, some straightforward quaternion mathematical operations are employed on the encrypted secret message and the cover HEVC frames to represent them in a quaternion form in the frequency domain, then the encrypted secret audio message is hidden within the cover HEVC frame. At the receiver, the secret message can be retrieved and extracted from the cover HEVC frame utilizing the same methodology of the employed quaternion mathematical operations. The major contributions of the suggested HEVC steganography scheme are: (1) it allows hiding of massive amount of secret information within cover video frames, and (2) it has higher robustness against multimedia attacks and steganalysis contrasted to the conventional and literature schemes. Furthermore, the proposed approach is evaluated utilizing different assessment metrics like Feature Similarity Index Measure (FSIM), Peak Signal-to-Noise Ratio (PSNR), correlation coefficient, and Structural Similarity Index Measure (SSIM) to evaluate the efficiency of the stego HEVC frames compared to the original ones. The achieved outcomes demonstrate that the suggested steganography scheme is straightforward to implement, more secure, and robust in the presence of steganalysis multimedia attacks compared to the literature approaches.

A hybrid image compression algorithm based on JPEG and Fuzzy transform

Abstract: We propose a new hybrid image compression algorithm which combines the F-transform and the JPEG. At first, we apply the direct F-transform and then, the JPEG compression. Conversly, the JPEG decompression is followed by the inverse F-transform to obtain the decompressed image. This scheme brings three benefits: (i) the direct F-transform filters out high frequencies so that the JPEG can reach a higher compression ratio; (ii) the JPEG color quantization can be omitted in order to achieve greater decompressed image quality; (iii) the JPEG-decompressed image is processed by by the inverse F-transform w.r.t. the adjoint partition almost lossless. The paper justifies the proposed hybrid algorithm by benchmarks which show that the hybrid algorithm achieves significantly higher decompressed image quality than the JPEG.