Quantization (image processing)

About: Quantization (image processing) is a research topic. Over the lifetime, 7977 publications have been published within this topic receiving 126632 citations.

System and method for processing image data using an image signal processor having back-end processing logic

Abstract: Disclosed embodiments provide for a an image signal processing system 32 that includes back-end pixel processing unit 120 that receives pixel data after being processed by at least one of a front-end pixel processing unit 80 and a pixel processing pipeline 82. In certain embodiments, the back-end processing unit 120 receives luma/chroma image data and may be configured to apply face detection operations, local tone mapping, bright, contrast, color adjustments, as well as scaling. Further, the back-end processing unit 120 may also include a back-end statistics unit 2208 that may collect frequency statistics. The frequency statistics may be provided to an encoder 118 and may be used to determine quantization parameters that are to be applied to an image frame.

Segmentation-based JPEG image artifacts reduction

Abstract: A method for reducing ringing and blocking artifacts in a decompressed image models an image in a relatively small area as several smooth regions separated by edges The method uses JPEG MxM pixel blocks and is compatible with JPEG decompression To reduce ringing, a block is examined for uniformity, segmented and smoothed Then, after a DCT transform, a projection is performed to guarantee that the DCT coefficients of the resulting image block will be within the initial quantization interval The resultant image is produced by an inverse DCT To reduce blocking, the method is modified to employ a large outer window for uniformity checking, segmentation and smoothing and a small inner window for DCT projection

Maximum likelihood estimation of JPEG quantization table in the identification of bitmap compression history

Abstract: To process previously JPEG coded images the knowledge of the quantization table used in compression is sometimes required. This happens for example in JPEG artifact removal and in JPEG re-compression. However, the quantization table might not be known due to various reasons. A method is presented for the maximum likelihood estimation (MLE) of the JPEG quantization tables. An efficient method is also provided to identify if an image has been previously JPEG compressed.

JPEG 2000: overview, architecture, and applications

Abstract: JPEG 2000 will soon be an international standard for still image compression. This paper describes that standard at a high level, indicates the component pieces which empower the standard, and gives example applications which highlight differences between JPEG 2000 and prior image compression standards.

Quantitative Analysis of Digital Microscope Images

Abstract: Publisher Summary The chapter discusses quantitative analysis of digital microscope images and presents several exercises to provide examples to explain the concept. The chapter also presents the basic concepts in quantitative analysis for imaging, but these concepts rest on a well-established foundation of signal theory and quantitative data analysis. The chapter presents several examples for understanding the imaging process as a transformation from sample to image and the limits and considerations of quantitative analysis. The chapter introduces to the concept of digitally correcting the images and also focuses on some of the more critical types of data transformation and some of the frequently encountered issues in quantization. Image processing represents a form of data processing. There are many examples of data processing such as fitting the data to a theoretical curve. In all these cases, it is critical that care is taken during all steps of transformation, processing, and quantization.