Perceptual Video Coding Based on SSIM-Inspired Divisive Normalization

Perceptual Video Coding Based on SSIM-Inspired Divisive Normalization is a report that focuses on the necessity of video coding. The proposed method can highlight the video coding based on the SSIM inspired divisive normalization approach. The perception model is dependent on the MB level and global quantization matrix. Significant gain in terms of the SSIM performance is easily achievable that can help in the perceptual video coding mechanism. A performance gain and a better visual quality are easily achievable that can help in ensuring a divisive normalization. The reduction of the storage space and bandwidth of the visual content production. The mini project report on abstract on perceptual video coding based on ssim-inspired divisive normalization is available. The users can free download abstract, synopsis on pdf to understand the effects of perceptual video coding based on ssim-inspired divisive normalization.

Perceptual video coding, which is a technique to video compression that is tuned to fit with human perceptual systems, is a state-of-the-art method that is based on Perceptual Video Coding Based on SSIM-Inspired Divisive Normalization of technological advancement. The Structural Similarity Index, often known as SSIM, is a measure that has gained widespread acceptance for evaluating the quality of compressed pictures. This index takes into account brightness, contrast, and structural elements of the image. The human visual system’s contrast sensitivity and dynamic range adaptation served as inspiration for the divisive normalization that was used in the suggested approach for perceptual video coding. This method was built on the foundation of SSIM and its concepts. By taking into consideration how sensitive human vision is to varying spatial and temporal frequencies, this method seeks to improve the perceived quality of compressed video footage. The approach in question was developed with that goal in mind.

Divisive normalization is a method that was inspired by the neuronal processing that was discovered in the human visual system. In this processing, reactions to stimuli are normalized depending on the total activity in the visual field that is around them. This normalizing technique is performed to the SSIM-inspired characteristics in the context of perceptual video coding. Doing so makes it possible for a more nuanced representation of perceptual quality to be generated. Divisive normalization helps address perceptual phenomena such as contrast masking, in which the visibility of some features is impacted by the presence of adjacent components, and it adds to the model’s capacity to adapt to various degrees of complexity in video material. One of these phenomena is contrast masking, and it occurs when the visibility of certain details is modified by the presence of nearby elements.

The enhancement of the Perceptual Video Coding Based on SSIM-Inspired Divisive Normalization features is accomplished using a normalizing procedure that takes into account both the local and the global context as part of the integration of divisive normalization into perceptual video coding. The coding model becomes more effective at collecting perceptually significant elements and ensuring that the process aligns closely with human visual perception when it takes into account the total visual context. This is achieved by ensuring that the overall visual context is taken into account. This is of utmost significance in video coding, where temporal nuances and spatial complexities call for an all-encompassing method of evaluating perceptual quality.

Application of Perceptual Video Coding Based on SSIM-Inspired Divisive Normalization , which is based on SSIM-inspired divisive normalization, has a wide variety of applications. Some examples of these applications include video streaming, multimedia communication, and virtual reality. The approach makes a contribution to the delivery of high-quality video material across networks with limited capacity while maintaining perceptual integrity in the context of video streaming. When it comes to multimedia communication, the perceptual coding technique guarantees that video material maintains its quality even at lower bitrates. This improves the user experience, whether they are participating in video conferencing or online collaboration. The approach assists in the effective compression of video information in virtual reality, where immersion and visual quality are of the utmost importance. At the same time, the method helps to preserve a perceptually fulfilling experience for users.

Perceptual video coding, which is emphasizes human perceptual systems in the compression of video footage and is based on SSIM-inspired divisive normalization, is a cutting-edge method that provides a new approach to the problem. The method achieves a balance between computational efficiency and perceptual quality by combining the principles of SSIM with divisive normalization. This makes it a valuable advancement in the field of video coding, particularly in applications where human visual experience is a primary consideration.

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Topics Covered:
01)Introduction
02)Objectives, ER Diagram
03)Flow Chats, Algorithms used
04)System Requirements
05)Project Screenshots
06)Conclusion, References