A Light Field Image Compression Method Based on Linear Transformation and Image Interpolation

Abstract

The invention discloses an optical field image compression method. The method comprises the following steps: inputting original optical field images f(x,y), performing early-stage data processing, and generating microlens array images L(x,y) in orthogonal arrangement; performing linear transformation on the microlens array images L(x,y), enabling multiple mutually overlapped macro pixel modules to be separate from each other and uniformly arranged, and forming regular optical field images Lt(x,y); performing interpolation on pixel points to be interpolated in the regular optical field images Lt(x,y); and according to format demands of an encoder, performing image or chroma space processing on the regular optical field images Lt(x,y), obtaining compressed decoded images by performing encoding and decoding on the regular optical field images Lt(x,y) after the image or chroma space processing by use of the encoder, performing image or chroma space inverse processing on the compressed decoded images, performing reverse linear transformation, and generating reconstruction images L'(x,y) in the same structure as the microlens array images L(x,y). The optical field image compression method based on the linear transformation and the interpolation, brought forward by the invention, prevents introduction of quite large calculation complexity and effectively improves the encoding efficiency.

Description

technical field [0001] The invention relates to the technical field of computer vision and digital image processing, in particular to a light field image compression method based on linear transformation and image interpolation. Background technique [0002] With the advent of consumer-grade handheld light field cameras, the function of taking pictures first and then focusing has attracted widespread attention. Different from traditional camera pictures, light field cameras can record light intensity information and light angle information at the same time due to their unique optical structure, and the resolution of light field images has also been greatly increased, causing the data volume of light field images to expand dramatically. With the extensive use of mobile terminal devices and the huge demand for real-time data transmission, such a huge amount of data will inevitably bring huge pressure to the storage and transmission of light field data, and will also restrict t...

AI Technical Summary

Problems solved by technology

The video-based compression scheme refers to extracting a series of sub-aperture images from the original light field data, and compressing the video sequence generated by the sub-aperture images based on existing video encoders such as H.265 or HEVC. Although this scheme is effective The coding efficiency is greatly improved, but the computational complexity is also greatly increased, which affects the real-time performance of coding.

On the basis of these two types of compression schemes, algorithms such as layered representation and compressed sensing are also introduced into the compression scheme. The introduction of these algorithms either needs to change the optical structure of the original camera, or bring huge complexity to the decoding end. Spend

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