افزایش وضوح و روشنایی تصاویر کم‌نور با استفاده از رویکرد RETINEX و تبدیل غیر خطی
محورهای موضوعی : مهندسی برق و کامپیوتر
مریم قاسمی
1
(دانشگاه فردوسی مشهد)
مرتضی خادمی
2
(دانشگاه فردوسی مشهد)
عباس ابراهیمی مقدم
3
(دانشگاه فردوسی مشهد)
کلید واژه: بهبود تصاویر کم‌نور, بهبود روشنایی و وضوح, تبدیل غیر خطی, روش‌های مبتنی بر رویکرد RETINEX,
چکیده مقاله :
تصاویر ضبط‌شده در شرایط نوری ضعیف دارای روشنایی و وضوح پایین و نویز زیاد هستند، لذا برای بینایی انسان و ماشین نامناسب بوده و در عملکرد آنها تأثیرات منفی می‌گذارند. تحقیقات زیادی برای بهبود چنین تصاویری انجام شده است. روش‌های پیشنهادشده برای حل این مسئله به میزان قابل توجهی این گونه تصاویر را بهبود می‌بخشند. یک دسته از این روش‌ها، روش‌های مبتنی بر رویکرد RETINEX هستند که باعث اصلاح تصاویر کم‌نور شده‌اند. اما از آنجا که ساختار اولیه این رویکرد پیچیده است و کارایی پایینی دارد، محققان روش‌های دیگری همچون SSR، MSR و MSRCR را برای رفع مشکل آن ارائه داده‌اند. این روش‌ها نیز به نوبه خود مشکلاتی همچون غیر طبیعی‌بودن تصاویر حاصل و تقویت نویز دارند. در این تحقیق با به دست آوردن مؤلفه روشنایی بهینه، استفاده از تبدیل غیر خطی و اعمال هموارسازی روی تصویر به عنوان مرحله پس‌پردازش، این نقاط ضعف تا حد زیادی رفع می‌شوند. با اعمال روش پیشنهادی، تصاویر پردازش‌شده ظاهری طبیعی‌تر داشته و اطلاعات آنها بیشتر حفظ شده است. برای ارزیابی روش پیشنهادی از معیارهای ذهنی و عینی همچون AFC2، IE، SSIM، PSNR و IMMSE استفاده شده است. نتایج شبیه‌سازی، نشان‌دهنده برتری روش پیشنهادی نسبت به روش‌های رقیب می‌باشد.
Images captured in low light conditions are unsuitable for human and machine vision due to low brightness and sharpness and high noise, and have a negative effect on their performance. Much research has been done to improve such images. The methods proposed so far to solve this problem greatly improve such images. One of these methods is the RETINEX-based method, which modifies low-light images, but because the initial structure of this method is complex and inefficient, researchers have developed other methods such as SSR, MSR, and MSRCR. To solve the problem, they have presented this approach. These methods, in turn, have problems such as abnormal images and amplification of noise. In the continuation of the work done, the field of optimization has been used, which shows better performance than the previous works. In this research, by obtaining the optimal brightness component, using nonlinear conversion and applying smoothing filter and reducing noise on the image as a post-processing step, these weaknesses are largely eliminated. By applying the proposed method, the resulting images look more natural and their information is more preserved. Subjective and objective criteria such as EI, SSIM, PSNR and IMMSE were used to evaluate the proposed method. The simulation results show the superiority of the proposed method over the competing methods.
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