yaya ne Lens Vignetting? Mada biyu da saboda Vignetting

A cikin tsarin fadin da ke zancen, abu mai kima da yawa da ke ƙarƙashin fadin wanda aka yiya shi ne shine lens vignetting ya sami sauye na ima. Ya kawo canzawa na gwiwa na ima ta hanyar kammawa da taƙaita, wanda ya kawo "effected dark corner". Idan wannan zai iya samun sauye a cikin litaccen litattafen, shine wani abu mai muhimmi a cikin tsarin fadin mai amfani da rashin fahimta.

A matsayin mai amsa wanda ke tsetsewa a cikin tsarin kamera, wannan maqala zai duba dukkan abin da ke kawo canzawa da zaɓi na vignetting, kuma muhimminshi a cikin fadin da ke zancen. Zamu duba yadda za a samu sauye da sauye wannan halin don tabbatar da tsarin fadin zai samu data mai tsauri da mai amintsi, wanda zai bace sabon asali don amfani daga cikin indasitiral automation zuwa zuwa zuwa kuma tsarin kula da kima.

Menene lens vignetting? Wani duba zuwa bayanin ma'ana na vignettes

An farko na lens shine a cikin fassaren fasaha wanda ke nufin cewa babban hoto ya zamu shine gasar karo. Wannan nufin karo da ba ta samu ba shine zai sa hoto ta karkatar da karo a kanso ko babban hoto. Ba ta da ke kasa da karo ba, amma shine wani abu da ke cire karo ta amfani da alama ko abubuwan da ke cikin nisa na lens.

Samun sauti na vignetting shine satar ilmin da kowane mai amfani da fasahar yanki ya kamata ya sani. Shine wani abu da ke nufin cewa bayanin hoto ta dadi ko toman da ke gaba. Don haka shine amsawa, zai iya duba cewa vignetting shine wani abu ne da ke nufin cewa karo ta kasa daga babban hoto zuwa babban hoto a lokacin da ke hada hoto. Wannan kasa shine daidai da nufin karo da ke cikin fasaha, wani abu da ya kamata ya sani da ya zamu daidai da fasaha.

Ƙimar ƙarin tace ya yi amfani da "stops of light," kuma kadan daban daban ya nuna rabin raman. Don samanin hoton mai amfani, tun tace na ƙarin kusan zai iya samar da ƙarin a cikin nisbi na idanƙarwa zuwa babbar kewayar (SNR) na bayanin hoton a daban-daban, don haka zai iya gwadawa aiki na algorithim.

Menene daban-daban da saboda tace?

Babu sabon guda daya na tace; iya kai tsakanin guda hudu:

Ƙarƙashin ƙarfe na ƙarfe: Wannan ya faru ne daga cikin abubuwan da ke gaban kamera, samaɗa suna da lens hoods, filter rings ko lens barrels. Wannan abubuwan zai iya taka rawar rawar a lokacin da suka gudu da kama. Misali, amfani da lens hood mai amfani da telephoto lens a kai na wide-angle lens zai iya samar da tace na ƙarin kusan.

Ƙarƙashin ƙirar ƙira: Wannan keɓe da iyakokin kudin ƙwararren da ke cikin ƙwararren. Lokacin da cikin tare da ƙwararren ya ƙaduwa da kama ƙarfi, shugaban ƙwararren, girman, da makon ƙwararren da ke cikin ƙwararren ya kula cikin ciki da ba su san karfi zuwa katsin sensor ba. Nau'in wannan vingetting ya ƙare lokacin da aka kankara shugaban kuma ya kasance mai karfi a lokacin da aka amfani da shugaban mai karfi.

Ƙarƙashin halitta: Wannan ita ce abin da ba za a iya kawo ba daban daban na fizik ɗin da ke nufin cos⁴θ. Hakan za a iya amfani da sauyin ƙwararren da ke cikin ƙwararren, karfi na cikin ya ƙare lokacin da yawan takaddun cikin (θ) ya ƙare. Wannan ya kasance mai karfi a cikin ƙwararren mai girma da girman sensor mai girma, kuma ita ce abin da ke cikin haka da ba za a iya rage ba tare da amfani da sauyin iyakokin.

Vignetting na Pixel: Wannan yana faruwa ne saboda bambancin kusurwar haske da aka karɓa ta gefen pixels idan aka kwatanta da pixels na tsakiya. Wannan bambanci yana haifar da sakamako mai duhu a kan pixels na kusurwa saboda ƙananan rage yawan haske da aka kama. Ba kamar zane-zane na gani ba, zane-zane na pixel shine halayyar halayyar zane na firikwensin kuma ba a rinjaye shi ta hanyar daidaitawa da maɓallin buɗewa ba. Wannan yana nufin cewa yayin da vigneting yawanci yana hade ne kawai tare da ruwan tabarau, yana iya faruwa saboda halayen firikwensin.

Menene vignet a cikin daukar hoto?

Wasanni masu aiki da kamera ke zamuwa a cikin kewayar kewayar kai tsaye kamar yadda ke nufin ilimin sanyawa. Kuna iya amfani da shi don nuna abubuwan da ke cikin hoto kuma tsara zarin halin wani abu. A yayin haka, a cikin sararin kewayar masu amfani da kamera ta jiki, halin wani abu ba shi da yin daban. Don saman kewayar masu iya amfani da kamera wanda zai buƙatar yi adadin mai zuwa, zaiyi halin wani abu ne da ke kuskyarsa tare da tattara bayanin. Zai iya kama abubuwan da ke cikin saitin kewayar su zogoo ta hanyar ƙarin rana ko kuma zai iya kama su zogoo bayanin rana da kuma nisa na launi.

Kewayar kamera ya ke so ƙima na nufin da kuma nufin ilimin halin wani abu, a yayin da kewayar masu iya amfani da kamera ya ke so tattara bayanin, iya wasuwa da sauri. Don algorithmon AI, babban farko na rana a cikin saitin kewayar da zahabin kewayar zai iya wasuwa kamar yadda ke nufin farko a cikin launi ko kuma nisa na abu, yana dacewa su zogoo. Don haka, a cikin kewayar masu iya amfani da kamera, zaiyi halin wani abu ba shi da yin daban amma shi ne da ya kamata a yi wahala da shi.

Mahimmancin a cikin imaging da ma'adinan al'ada. Fasaha da zauna ta hanyar tacewa

A cikin embedded vision da ma'adinan al'ada, ba za a iya sami kuskure da nega ta hanyar tacewa. Tacewa ta kawo ƙarshi zuwa tsakanin fadin zuwa, ta haifar da tacewa a cikin rashin tsawo, kusurwa da launuka a karkashin zuwa. Wannan ya kawo alhakin zuwa masu alhakin gama gari kamar yadda suka shafi launuka, kirkiran zuwa da karkashin abu.

Abin da ke sau da tacewa shine ƙarin yawan signal-to-noise ratio (SNR) a cikin karkashin zuwa, ta hanyar tacewa zuwa rashin kwaliti na zuwa da kuskure na alamar zuwa a cikin wadannan yankuna. Tacewa shine abin da ya dace masu alhakin gama gari wanda ke bukatar tacewa mai tsauri, nasarar alamar kuskure ko na ukwuren launuka. Misali, a cikin masu alhakin kwaliti na sarrafa, abin da ke karkashin zuwan da ke kuskure zai iya sami kuskure ta hanyar rashin iluminashen, ta hanyar kuskure na bukata alhakin sarrafa.

A cikin rashin 3D, zai iya kuma saman kwayoyin a cikin algorithmen kan layi, wanda ya dacewa da kwayoyin a cikin rashin 3D da aka saita a gaba. Don haka, yin aiki da vignetting shine ma'aliya mai muhimmi a cikin wani system na gani da kele na iya buƙatun ainihin hoton.

Yaya A Kokarin Da Karyar Vignetting? Vignette Camera Selection Da Calibration

Kokarin da karyar lens vignetting shine tsarin da ke taka lele daban-daban wanda ya buƙata aiki guda biyu a cikin tsarin harware da saftware.

Amsawa Na Harware

• Zazzabi Na Lens: Zi lens mai iyaye da mai kyau. Lenses na farko sune ba da aiki mai kyau a karyar vignetting yana da zoom lenses. Daidaitan hoton na lens ya kamata ya kasance girma, ko kama da girman sensor na hoton da ake amfani da ita.
• Kokarin Aperture: Yi raman daidai (kuma ake kira shi da "stopping down"). Don fito na optiko, stopping down na aperture ya taimake raman daidai ya rabawa kansu cewa light ya yi blocked da abubuwan lenti, don haka ya rabawa darajar fito. Amma, sani cewa daya da stopping down na aperture zai iya shiga abin da ke kawo kuskurewa, wanda zai iya kuma yin raman daidai.
• Tsauawa na Sistima: Samsu cewa lensi ta wuya ta dacewa da abubuwan guda-guda kamar wadannan camera Module da kuma filatin don nuna fito na makaniki.

Amsa na Software

• Tsauawa na Flat-Field (FFC): Wannan shine shi ne a cikin ƙwayoyin da suka faɗa kuma yin tattauna a al'adun tattara. A cikin madadunsa shine yin "tattaunan tattara" don kuiwa. Faru, sami fadin ƙwayo ko ƙwayon gray a cikin sama daya (flat-field image). Dangane, sami fadin dark-field a cikin ba su da sama (dark frame image). A yayin amfani da waɗannan fadu biyu, algorith can nuna coefficient na kewayon kewayo don kowane pixel kuma ya yi inverse compensation a kowane fadin da ke gaba a cikin tsoro na fadin.
• Look-Up Table (LUT): A cikin wasu tsarin da ke so da kima da kai tsaron, kusan tattarawa zai iya amfani da LUT sai an yi rashin alamar cikin amfani da processing mai kyau.

Lokacin da za a zaɓi kwayon kuiwa don sistema na embedded vision, inzinzameni dole ne su yi amfani da al'adun kuiwar kwayo kuma su rarraba tsarin tattara na software masu zuwa.

Kuiwar a cikin Embedded Vision Systems

A cikin saitin vision na-embe, ba za a iya haifar da isassun kwalla ba. Yana daya da zaɓin tare da sauye na saiti. Ko za a yi amfani da shi don gyara abubu da ke wasan iyakawa ko faɗin mallin mutum a cikin tattara kwalla, hoton da aka yiya da isassun kwalla zai iya haifar da batun algorithumin saitin mutum ya kawo alama.

Don haka, fahimtar luro na kwalla da kuma amfani da ma'aurata na kuskyau na muhimmi don watsa saitin saitin vision na-embe da ke da uku da sauye. Lokacin da karkatar saitin saitin vision na-embe, dole ne a sami batun kuskure na kwalla azaman ma'aurata na asali. Zaɓin luro mai zurfi mai yawa, da kuma algorithumin kuskure na flat-field mai zurfi, shine daidaitan a cikin kusurwa da daga waɗancan abubu.

Tsarin fadarwa na iya nuna aiki ba ta yiwuwa da algorithmon da ke ƙarƙashin sa kuma ba tare da tsohon hardware da bayanan hoton ta san. Tame da kewayon lens ta yiwuwa sosai don nuna tsohon bayanai da kuma wani challenge da injinin koyaya na iya nuna dole ne su duba wajen rana da saukacen sa.

Muchvision ta offerin halin tare da kewayon lens

Shin kuma kake da shakka da tsawon kewayon a cikin gaban hoton a cikin projeciton na iya nuna? Tuntu karshenmu na mutane-mutane a yau da mu maida muku halin tare da zaɓin lens da halin tare da kewayon lens don nuna yin tsoho ya samen data mai kyau!