Image processing device and method

Abstract

Provided are an image processing device and method. The image processing apparatus includes: a zero-level detecting unit that detects a zero-level in which a frequency of occurrence of a pixel value is zero from among a plurality of levels that classify pixel values ​​of an image according to pixel value sizes; and a non-zero-level converting unit that converts a pixel value by The range of zero levels detected by the zero level detection unit is updated, and the zero levels are converted into non-zero levels whose occurrence frequency of pixel values ​​is 1 or higher without updating the total number of levels. The present invention can be applied to an image processing device.

Description

technical field [0001] The present invention relates to an image processing device and method, and more particularly, to an image processing device and method capable of suppressing quantization errors. Background technique [0002] In the prior art, a bit conversion technique for performing conversion from a high bit depth to a low bit depth is often used as a quantization technique for image processing and the like. In other words, an N-bit image is converted into an L-bit image (N>L) by quantization processing. On the other hand, inverse conversion processing from low bit depth to high bit depth corresponds to inverse quantization. A linear quantization technique is often used as an image quantization technique. However, linear quantization techniques are computationally inexpensive but have relatively large quantization errors. For this reason, when a high-bit-depth image is converted to a low-bit-depth image by quantization, and then the low-bit-depth image is con...

AI Technical Summary

Problems solved by technology

However, linear quantization techniques are computationally inexpensive but have relatively large quantization errors

For this reason, when a high-bit-depth image is converted to a low-bit-depth image by quantization, and then the low-bit-depth image is converted to a high-bit-depth image by inverse quantization (returning to the original bit-depth), the recovered high-bit-depth image (images that have undergone quantization and inverse quantization processing) may be significantly degraded compared to the original image (image before quantization and inverse quantization processing)

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