Faculty Publications

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Author: search.filters.author.Sushma, B.Subject: search.filters.subject.Video signal processing

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    Distributed video coding based on classification of frequency bands with block texture conditioned key frame encoder for wireless capsule endoscopy
    (Elsevier Ltd, 2020) Sushma, B.; Aparna., P.
    Wireless capsule endoscopy (WCE) has provided remarkable improvement in diagnosing gastrointestinal disorders by scanning the entire digestive tract. The system still need refinement, to upgrade the quality of images, frame rate and battery life. The principal component of the system that can address these issues is low complexity video compressor. Motivated by low computational complexity requirements of WCE video encoding, this paper presents a distributed video coding framework based on frequency bands classification. The lower frequency bands are used to generate good quality side information (SI) as they exhibit high temporal correlation. This reduces the complexity of hash generation at the encoder, thus eliminating the latency in SI creation. Apart from this, SI creation involves only a simple block search and doesn't depend on Wyner–Ziv (WZ) bands. Also different approach for distributed coding of sub-sampled chroma components of WZ frame is proposed. Low complexity JPEG based key frame encoding is proposed that take advantage of WCE image textural properties to reduce the complexity of encoding smooth blocks by 81% at the quantization and encoding stage. Other novel features include use of discrete Tchebichef transform (DTT), Golomb–Rice code for entropy coding. Performance evaluation shows that the proposed method achieves 60% improvement in compression over Motion JPEG with low computational complexity. © 2020 Elsevier Ltd
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    Deep chroma prediction of Wyner–Ziv frames in distributed video coding of wireless capsule endoscopy video
    (Academic Press Inc., 2022) Sushma, B.; Aparna., P.
    Compression of captured video frames is crucial for saving the power in wireless capsule endoscopy (WCE). A low complexity encoder is desired to limit the power consumption required for compressing the WCE video. Distributed video coding (DVC) technique is best suitable for designing a low complexity encoder. In this technique, frames captured in RGB colour space are converted into YCbCr colour space. Both Y and CbCr representing luma and chroma components of the Wyner–Ziv (WZ) frames are processed and encoded in existing DVC techniques proposed for WCE video compression. In the WCE video, consecutive frames exhibit more similarity in texture and colour properties. The proposed work uses these properties to present a method for processing and encoding only the luma component of a WZ frame. The chroma components of the WZ frame are predicted by an encoder–decoder based deep chroma prediction model at the decoder by matching luma and texture information of the keyframe and WZ frame. The proposed method reduces the computations required for encoding and transmitting of WZ chroma component. The results show that the proposed DVC with a deep chroma prediction model performs better when compared to motion JPEG and existing DVC systems for WCE at the reduced encoder complexity. © 2022 Elsevier Inc.